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{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "b12491cf-cfa0-4df4-bd53-6683ec4d686c",
"_uuid": "3d0d3f64bab223aa8869e80742d008343b9006ae"
},
"source": [
"Predict whether an adult's income exceeds or is below $50K/yr based on census data. Data Analysis, Data visualization, Feature Selection and Reduction, about 10 Machine Learning models/estimators. Multilayer Perceptron(Deep Learning/Artificial Neural Network). Dataset splitted into training and testing data."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"_cell_guid": "98d1a824-d4aa-4a62-8fa9-942dccc0f8d9",
"_uuid": "cf2b91e9d9dfe5154175b2e4b26882a54c1da76f"
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Using TensorFlow backend.\n"
]
}
],
"source": [
"import numpy\n",
"import pandas\n",
"from sklearn.feature_selection import SelectKBest\n",
"from sklearn.feature_selection import chi2\n",
"from sklearn.feature_selection import RFE\n",
"from sklearn.linear_model import LogisticRegression\n",
"from sklearn.decomposition import PCA\n",
"from sklearn.ensemble import ExtraTreesClassifier\n",
"\n",
"\n",
"import matplotlib.pyplot as plt\n",
"from pandas.tools.plotting import scatter_matrix\n",
"\n",
"from sklearn.model_selection import train_test_split\n",
"from sklearn.linear_model import LogisticRegression\n",
"from sklearn.tree import DecisionTreeClassifier\n",
"from sklearn.neighbors import KNeighborsClassifier\n",
"from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n",
"from sklearn.naive_bayes import GaussianNB\n",
"from sklearn.svm import SVC\n",
"from sklearn.svm import LinearSVC\n",
"from sklearn.linear_model import SGDClassifier\n",
"from sklearn.metrics import accuracy_score\n",
"from sklearn.metrics import mean_squared_error\n",
"\n",
"\n",
"\n",
"from keras.models import Sequential\n",
"from keras.layers import Dense\n",
"from keras.layers import Dropout\n",
"from keras.constraints import maxnorm\n",
"\n",
"# fix random seed for reproducibility\n",
"seed = 7\n",
"numpy.random.seed(seed)\n"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"_cell_guid": "fcecd2f4-c044-4f40-92b7-6b8df8cb6615",
"_uuid": "a4b5029576d1ea654b51bd077db67f7f58125a2f",
"collapsed": true
},
"outputs": [],
"source": [
"# load dataset\n",
"dataframe = pandas.read_csv(\"../input/adult.csv\")\n",
"\n",
"dataframe = dataframe.replace({'?': numpy.nan}).dropna()\n"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"_cell_guid": "65871ef4-b118-49f3-923e-2f51c84f8b44",
"_uuid": "9be02e875994e00917a44f7ee480fd97d59f7ba8",
"collapsed": true
},
"outputs": [],
"source": [
"\n",
"# Assign names to Columns\n",
"dataframe.columns = ['age', 'workclass', 'fnlwgt', 'education', 'education_num', 'marital_status', 'occupation', 'relationship', 'race', 'sex', 'capital_gain', 'capital_loss', 'hours_per_week', 'native_country', 'income']\n",
"\n",
"# Encode Data\n",
"dataframe.workclass.replace(('Private', 'Self-emp-not-inc', 'Self-emp-inc', 'Federal-gov', 'Local-gov', 'State-gov', 'Without-pay', 'Never-worked'),(1,2,3,4,5,6,7,8), inplace=True)\n",
"dataframe.education.replace(('Bachelors', 'Some-college', '11th', 'HS-grad', 'Prof-school', 'Assoc-acdm', 'Assoc-voc', '9th', '7th-8th', '12th', 'Masters', '1st-4th', '10th', 'Doctorate', '5th-6th', 'Preschool'),(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16), inplace=True)\n",
"dataframe.marital_status.replace(('Married-civ-spouse', 'Divorced', 'Never-married', 'Separated', 'Widowed', 'Married-spouse-absent', 'Married-AF-spouse'),(1,2,3,4,5,6,7), inplace=True)\n",
"dataframe.occupation.replace(('Tech-support', 'Craft-repair', 'Other-service', 'Sales', 'Exec-managerial', 'Prof-specialty', 'Handlers-cleaners', 'Machine-op-inspct', 'Adm-clerical', 'Farming-fishing', 'Transport-moving', 'Priv-house-serv', 'Protective-serv', 'Armed-Forces'),(1,2,3,4,5,6,7,8,9,10,11,12,13,14), inplace=True)\n",
"dataframe.relationship.replace(('Wife', 'Own-child', 'Husband', 'Not-in-family', 'Other-relative', 'Unmarried'),(1,2,3,4,5,6), inplace=True)\n",
"dataframe.race.replace(('White', 'Asian-Pac-Islander', 'Amer-Indian-Eskimo', 'Other', 'Black'),(1,2,3,4,5), inplace=True)\n",
"dataframe.sex.replace(('Female', 'Male'),(1,2), inplace=True)\n",
"dataframe.native_country.replace(('United-States', 'Cambodia', 'England', 'Puerto-Rico', 'Canada', 'Germany', 'Outlying-US(Guam-USVI-etc)', 'India', 'Japan', 'Greece', 'South', 'China', 'Cuba', 'Iran', 'Honduras', 'Philippines', 'Italy', 'Poland', 'Jamaica', 'Vietnam', 'Mexico', 'Portugal', 'Ireland', 'France', 'Dominican-Republic', 'Laos', 'Ecuador', 'Taiwan', 'Haiti', 'Columbia', 'Hungary', 'Guatemala', 'Nicaragua', 'Scotland', 'Thailand', 'Yugoslavia', 'El-Salvador', 'Trinadad&Tobago', 'Peru', 'Hong', 'Holand-Netherlands'),(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41), inplace=True)\n",
"dataframe.income.replace(('<=50K', '>50K'),(0,1), inplace=True)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"_cell_guid": "4800f357-87c1-4f6a-9a47-2e049e9ca9d6",
"_uuid": "ec2e60262d9eae5f3203bd40a0c176ce76d12fdf"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Head: age workclass fnlwgt education education_num marital_status \\\n",
"1 82 1 132870 4 9 5 \n",
"3 54 1 140359 9 4 2 \n",
"4 41 1 264663 2 10 4 \n",
"5 34 1 216864 4 9 2 \n",
"6 38 1 150601 13 6 4 \n",
"\n",
" occupation relationship race sex capital_gain capital_loss \\\n",
"1 5 4 1 1 0 4356 \n",
"3 8 6 1 1 0 3900 \n",
"4 6 2 1 1 0 3900 \n",
"5 3 6 1 1 0 3770 \n",
"6 9 6 1 2 0 3770 \n",
"\n",
" hours_per_week native_country income \n",
"1 18 1 0 \n",
"3 40 1 0 \n",
"4 40 1 0 \n",
"5 45 1 0 \n",
"6 40 1 0 \n"
]
}
],
"source": [
"print(\"Head:\", dataframe.head())"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"_cell_guid": "89fa5e20-2e2b-4a25-b708-9969861aa33b",
"_uuid": "61ed92b5fced369e6b61fdef038c6a180e54326e"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Statistical Description: age workclass fnlwgt education education_num \\\n",
"count 30162.000000 30162.000000 3.016200e+04 30162.000000 30162.000000 \n",
"mean 38.437902 1.736788 1.897938e+05 4.372820 10.121312 \n",
"std 13.134665 1.461908 1.056530e+05 3.429379 2.549995 \n",
"min 17.000000 1.000000 1.376900e+04 1.000000 1.000000 \n",
"25% 28.000000 1.000000 1.176272e+05 2.000000 9.000000 \n",
"50% 37.000000 1.000000 1.784250e+05 4.000000 10.000000 \n",
"75% 47.000000 2.000000 2.376285e+05 5.000000 13.000000 \n",
"max 90.000000 7.000000 1.484705e+06 16.000000 16.000000 \n",
"\n",
" marital_status occupation relationship race sex \\\n",
"count 30162.000000 30162.000000 30162.000000 30162.000000 30162.000000 \n",
"mean 2.053213 5.742159 3.393276 1.445196 1.675685 \n",
"std 1.170881 2.978754 1.229789 1.196958 0.468126 \n",
"min 1.000000 1.000000 1.000000 1.000000 1.000000 \n",
"25% 1.000000 3.000000 3.000000 1.000000 1.000000 \n",
"50% 2.000000 5.000000 3.000000 1.000000 2.000000 \n",
"75% 3.000000 8.000000 4.000000 1.000000 2.000000 \n",
"max 7.000000 14.000000 6.000000 5.000000 2.000000 \n",
"\n",
" capital_gain capital_loss hours_per_week native_country \\\n",
"count 30162.000000 30162.000000 30162.000000 30162.000000 \n",
"mean 1092.007858 88.372489 40.931238 2.515583 \n",
"std 7406.346497 404.298370 11.979984 5.641075 \n",
"min 0.000000 0.000000 1.000000 1.000000 \n",
"25% 0.000000 0.000000 40.000000 1.000000 \n",
"50% 0.000000 0.000000 40.000000 1.000000 \n",
"75% 0.000000 0.000000 45.000000 1.000000 \n",
"max 99999.000000 4356.000000 99.000000 41.000000 \n",
"\n",
" income \n",
"count 30162.000000 \n",
"mean 0.248922 \n",
"std 0.432396 \n",
"min 0.000000 \n",
"25% 0.000000 \n",
"50% 0.000000 \n",
"75% 0.000000 \n",
"max 1.000000 \n"
]
}
],
"source": [
"print(\"Statistical Description:\", dataframe.describe())"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"_cell_guid": "098fe3fb-3595-44d9-9f70-6a49b4a05ad7",
"_uuid": "abe289fa6ccca423fd8498b8e1cb720e3f463783"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Shape: (30162, 15)\n"
]
}
],
"source": [
"print(\"Shape:\", dataframe.shape)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"_cell_guid": "77c63927-7816-4a6c-86ef-1c3400bb9f16",
"_uuid": "984ccc3d4a132db07c6ea3c3685e0084f9c0ce68"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Data Types: age int64\n",
"workclass int64\n",
"fnlwgt int64\n",
"education int64\n",
"education_num int64\n",
"marital_status int64\n",
"occupation int64\n",
"relationship int64\n",
"race int64\n",
"sex int64\n",
"capital_gain int64\n",
"capital_loss int64\n",
"hours_per_week int64\n",
"native_country int64\n",
"income int64\n",
"dtype: object\n"
]
}
],
"source": [
"print(\"Data Types:\", dataframe.dtypes)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"_cell_guid": "f235cfe0-e877-4bd0-9f6c-1d49f19bcc68",
"_uuid": "18746d8ae1a1401797ab6befb2f973c3452f4ef2"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Correlation: age workclass fnlwgt education education_num \\\n",
"age 1.000000 0.135486 -0.076511 0.115389 0.043526 \n",
"workclass 0.135486 1.000000 -0.026818 0.033766 0.179178 \n",
"fnlwgt -0.076511 -0.026818 1.000000 0.021349 -0.044992 \n",
"education 0.115389 0.033766 0.021349 1.000000 -0.232986 \n",
"education_num 0.043526 0.179178 -0.044992 -0.232986 1.000000 \n",
"marital_status -0.229179 -0.054710 0.028843 -0.014321 -0.103014 \n",
"occupation 0.022717 0.128779 0.003759 0.012513 -0.039235 \n",
"relationship 0.122997 0.013467 0.015271 0.028990 -0.033293 \n",
"race -0.023827 0.034985 0.099251 0.007865 -0.079069 \n",
"sex 0.081993 -0.005317 0.025362 0.032919 0.006157 \n",
"capital_gain 0.080154 0.013702 0.000422 0.022472 0.124416 \n",
"capital_loss 0.060165 0.022541 -0.009750 0.020413 0.079646 \n",
"hours_per_week 0.101599 0.027519 -0.022886 0.010587 0.152522 \n",
"native_country -0.035854 -0.055750 0.101715 0.160304 -0.164779 \n",
"income 0.241998 0.085662 -0.008957 0.009567 0.335286 \n",
"\n",
" marital_status occupation relationship race sex \\\n",
"age -0.229179 0.022717 0.122997 -0.023827 0.081993 \n",
"workclass -0.054710 0.128779 0.013467 0.034985 -0.005317 \n",
"fnlwgt 0.028843 0.003759 0.015271 0.099251 0.025362 \n",
"education -0.014321 0.012513 0.028990 0.007865 0.032919 \n",
"education_num -0.103014 -0.039235 -0.033293 -0.079069 0.006157 \n",
"marital_status 1.000000 0.017642 0.367944 0.132562 -0.383107 \n",
"occupation 0.017642 1.000000 0.011345 0.042565 -0.044658 \n",
"relationship 0.367944 0.011345 1.000000 0.121136 -0.179051 \n",
"race 0.132562 0.042565 0.121136 1.000000 -0.118940 \n",
"sex -0.383107 -0.044658 -0.179051 -0.118940 1.000000 \n",
"capital_gain -0.073526 -0.012190 -0.026872 -0.020829 0.048814 \n",
"capital_loss -0.069384 -0.014490 -0.031758 -0.028397 0.047011 \n",
"hours_per_week -0.226755 0.039834 0.052894 -0.061667 0.231268 \n",
"native_country 0.052469 0.000850 0.043989 0.054023 0.000595 \n",
"income -0.378684 -0.045129 -0.179116 -0.096061 0.216699 \n",
"\n",
" capital_gain capital_loss hours_per_week native_country \\\n",
"age 0.080154 0.060165 0.101599 -0.035854 \n",
"workclass 0.013702 0.022541 0.027519 -0.055750 \n",
"fnlwgt 0.000422 -0.009750 -0.022886 0.101715 \n",
"education 0.022472 0.020413 0.010587 0.160304 \n",
"education_num 0.124416 0.079646 0.152522 -0.164779 \n",
"marital_status -0.073526 -0.069384 -0.226755 0.052469 \n",
"occupation -0.012190 -0.014490 0.039834 0.000850 \n",
"relationship -0.026872 -0.031758 0.052894 0.043989 \n",
"race -0.020829 -0.028397 -0.061667 0.054023 \n",
"sex 0.048814 0.047011 0.231268 0.000595 \n",
"capital_gain 1.000000 -0.032229 0.080432 -0.017108 \n",
"capital_loss -0.032229 1.000000 0.052417 -0.020918 \n",
"hours_per_week 0.080432 0.052417 1.000000 -0.018839 \n",
"native_country -0.017108 -0.020918 -0.018839 1.000000 \n",
"income 0.221196 0.150053 0.229480 -0.059455 \n",
"\n",
" income \n",
"age 0.241998 \n",
"workclass 0.085662 \n",
"fnlwgt -0.008957 \n",
"education 0.009567 \n",
"education_num 0.335286 \n",
"marital_status -0.378684 \n",
"occupation -0.045129 \n",
"relationship -0.179116 \n",
"race -0.096061 \n",
"sex 0.216699 \n",
"capital_gain 0.221196 \n",
"capital_loss 0.150053 \n",
"hours_per_week 0.229480 \n",
"native_country -0.059455 \n",
"income 1.000000 \n"
]
}
],
"source": [
"print(\"Correlation:\", dataframe.corr(method='pearson'))"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "968c5f44-947e-41b0-b8b0-9213e2cf378a",
"_uuid": "3c68ee6dd716450076ec95bab8a3aa3c9f53c321"
},
"source": [
"'marital_status' has the highest correlation with the level of income(which is a negative correlation), followed by 'education_num' which is a positive correlation, 'fnlwgt' has the least correlation "
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"_cell_guid": "d983d519-ba16-4caf-bda2-f23590b91a3b",
"_uuid": "d3d8dcea4c35ced98f1862b1aa187a6a31a98781",
"collapsed": true
},
"outputs": [],
"source": [
"dataset = dataframe.values\n",
"\n",
"\n",
"X = dataset[:,0:14]\n",
"Y = dataset[:,14] "
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"_cell_guid": "b824f138-ab34-4090-9324-b2e70df1b093",
"_uuid": "b17caaf79d7b97baf0a0bd8a1d382f405a410a1e"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[ 7.928e+03 2.723e+02 1.423e+05 7.424e+00 2.178e+03 2.888e+03\n",
" 9.492e+01 4.313e+02 2.759e+02 1.852e+02 7.413e+07 1.256e+06\n",
" 5.569e+03 1.349e+03]\n",
"[[132870 0 4356]\n",
" [140359 0 3900]\n",
" [264663 0 3900]\n",
" [216864 0 3770]\n",
" [150601 0 3770]\n",
" [ 88638 0 3683]\n",
" [422013 0 3683]\n",
" [172274 0 3004]\n",
" [164526 0 2824]\n",
" [129177 0 2824]]\n"
]
}
],
"source": [
"# feature extraction\n",
"test = SelectKBest(score_func=chi2, k=3)\n",
"fit = test.fit(X, Y)\n",
"\n",
"# scores\n",
"numpy.set_printoptions(precision=3)\n",
"print(fit.scores_)\n",
"features = fit.transform(X)\n",
"\n",
"# summarise selected features\n",
"print(features[0:10,:])"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "2378b1f5-15dc-41c4-aee9-5a224a655ddd",
"_uuid": "fae50098caf3188ebfdec383dd1e8368ab6c26f1"
},
"source": [
" 'relationship', 'capital_loss' and 'capital_gain' were top 3 selected features for predicting 'Income'\n",
" using chi-squared (chi2) statistical test, Univariate Selections"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"_cell_guid": "cdb8c266-3830-489e-a319-0a71a42e2340",
"_uuid": "66e66e8eeb6a7f04f749aa2d7a27081781114114"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Number of Features: 3\n",
"Selected Features: [False False False False True True False False False True False False\n",
" False False]\n",
"Feature Ranking: [ 4 9 12 8 1 1 5 2 3 1 11 10 6 7]\n"
]
}
],
"source": [
"#Feature Selection\n",
"model = LogisticRegression()\n",
"rfe = RFE(model, 3)\n",
"fit = rfe.fit(X, Y)\n",
"\n",
"print(\"Number of Features: \", fit.n_features_)\n",
"print(\"Selected Features: \", fit.support_)\n",
"print(\"Feature Ranking: \", fit.ranking_)"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "6aab0237-9f15-4f14-8b62-c9d26fd323bf",
"_uuid": "5e40eb8cb4942a4d8b22622f91c14e8023cd1574"
},
"source": [
"'education_num', 'marital_status' and 'sex' were top 3 selected features/feature combination for predicting 'Income'\n",
" using Recursive Feature Elimination, the 1st and 2n are atually the two attributes with the highest correlation with the \n",
" 'Income' class"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "0c70b30b-bda5-4997-aedc-3fbfc1f7c925",
"_uuid": "88668e84b2da99806c93d38f06ff3b24e29e214e"
},
"source": [
" Dimensionality Reduction: Principal Component Analysis: "
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"_cell_guid": "0e129fde-2952-498f-ab29-dfdcbec3bdd2",
"_uuid": "efb5a57750ac48966f58ffd6fdcdfe6e48f9b5c5"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Explained Varience: [ 9.951e-01 4.890e-03 1.456e-05]\n"
]
}
],
"source": [
"pca = PCA(n_components=3)\n",
"fit = pca.fit(X)\n",
"\n",
"print(\"Explained Varience: \", fit.explained_variance_ratio_)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"_cell_guid": "75dcbe43-339b-4057-bb85-246e48f6f1a4",
"_uuid": "93301f27f71cebb2a8f20f7708eda6eeb051f229"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Feature Importance: [ 0.153 0.04 0.166 0.026 0.093 0.123 0.084 0.047 0.014 0.028\n",
" 0.09 0.027 0.094 0.016]\n"
]
}
],
"source": [
"model = ExtraTreesClassifier()\n",
"model.fit(X, Y)\n",
"print(\"Feature Importance: \", model.feature_importances_)\n"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"_cell_guid": "014fa872-0d5a-433f-b56b-cde75e3d2bcd",
"_uuid": "dc0d519dc730703d06c4b8a37c1af1fd8106fc72",
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "3772e92f-f2ff-448a-84ac-dfb0c43b8d04",
"_uuid": "07a0bc2c0491a810723802ae8b2918754327bdb6"
},
"source": [
"'age', 'fnlwgt' and 'marital_status' are the top 3 features using Feature Importance from Extra Trees(Bagged decision trees)"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "2b9038d9-0e2e-49a3-9f9e-83bc195e5dbf",
"_uuid": "8b4e5c377bafdb3a3ce68d1d0ef7d3a418bd0e78"
},
"source": [
"**VISUALIZATION**"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"_cell_guid": "1be197bc-ce47-40ae-b248-f63973e0e78a",
"_uuid": "f85b1d5881d780888a14d60672f15beb3bb21b0b"
},
"outputs": [
{
"data": {
"text/plain": [
"(array([ 22654., 0., 0., 0., 0., 0., 0.,\n",
" 0., 0., 7508.]),\n",
" array([ 0. , 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1. ]),\n",
" <a list of 10 Patch objects>)"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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cc8PMeT/wUlX9APhBkkeA9wKLMRyGme8ngBtr4mL8eJJngZ8FHluYFkdiXj+/TuXLSsN8\nJcdu4Op2138D8GpVHVzoRufQtHNOcgHwJeDjp8hvkdPOuaourKrVVbUauA+4dhEHAwz33/b9wPuT\nLEvy48AvAU8vcJ9zZZj5fpeJsySSrAR+BvjOgna58Ob18+uUPXOo43wlR5Lfbuv/nIknV64AxoH/\nYeK3j0VryDn/PnAOcGv7TfpILeIvLRtyzqeUYeZcVU8n+RrwLeBN4HNVNeUjkSe7If+N/xC4K8le\nJp7e+XRVLepvak3yBeAyYHmS/cBngbfAwnx++RfSkqTOqXxZSZI0Q4aDJKljOEiSOoaDJKljOEiS\nOoaDJKljOEiSOoaDJKnzf3xTQUKjxpYqAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fb54d913080>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.hist((dataframe.income))"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "f3510c59-3458-4037-a459-e92129d113c2",
"_uuid": "fa2bf1c17475f8c253dbaab1ce9992d7e49c871d"
},
"source": [
"Most of the dataset's samples fall within the '<=50K' 'income' output class"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"_cell_guid": "c2e700c1-1f11-482a-9f1e-526abf355fb6",
"_uuid": "aefb70860782f344afb4d6c9663787c0692adb1a"
},
"outputs": [
{
"data": {
"text/plain": [
"array([[<matplotlib.axes._subplots.AxesSubplot object at 0x7fb54d8d6940>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7fb5480ad898>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7fb54d98af28>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7fb528324160>],\n",
" [<matplotlib.axes._subplots.AxesSubplot object at 0x7fb5282862e8>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7fb528286320>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7fb5281df8d0>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7fb52819ccf8>],\n",
" [<matplotlib.axes._subplots.AxesSubplot object at 0x7fb52812e240>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7fb5280bb5c0>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7fb520505080>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7fb5204e1748>],\n",
" [<matplotlib.axes._subplots.AxesSubplot object at 0x7fb520449e80>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7fb520433160>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7fb5203a8dd8>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7fb52030e748>]], dtype=object)"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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xXmwzq7Zd/voyFnswCvf/nwmGMwLYqLaenmlUvZ5DbU059FqDTOJYbK27EhvN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\nAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fb54da359b0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"dataframe.hist()"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"_cell_guid": "4ddf5bdb-74e3-4a0b-b6b3-752f803c4a5b",
"_uuid": "a324658f3513a325fb0d3aac472e8ff7708fa4eb"
},
"outputs": [
{
"data": {
"text/plain": [
"array([[<matplotlib.axes._subplots.AxesSubplot object at 0x7fb506792630>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7fb506722390>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7fb506746c88>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7fb5066c9f98>],\n",
" [<matplotlib.axes._subplots.AxesSubplot object at 0x7fb506661588>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7fb5066daf98>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7fb50657b780>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7fb5064e5dd8>],\n",
" [<matplotlib.axes._subplots.AxesSubplot object at 0x7fb5064ce198>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7fb506442e10>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7fb5063a9780>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7fb506365b70>],\n",
" [<matplotlib.axes._subplots.AxesSubplot object at 0x7fb50633d6d8>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7fb5062f56d8>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7fb50628e0f0>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7fb506299d68>]], dtype=object)"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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51jj14uTkxObNm6uk9+/fn4ceegi9Xs9tt93GxIkTASVS59q1ay35IiIi2L17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\n7Z3ldS90qxGh/Ws1JZcElxPpd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"text/plain": [
"<matplotlib.figure.Figure at 0x7fb50678bc88>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"dataframe.plot(kind='density', subplots=True, layout=(4,4), sharex=False, sharey=False)"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "d808a383-e109-42e5-84bf-b55a8f857724",
"_uuid": "a200bbc8531b36599af421ee8def3740c15e173f"
},
"source": [
"There are a mixture of positive skews and negative skews the other attributes"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"_cell_guid": "6f539794-3108-44da-adf5-3f5a461d3ee6",
"_uuid": "c0352917df1d9dd79a5739792c5ad15a49ac60ef"
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py:1: FutureWarning: 'pandas.tools.plotting.scatter_matrix' is deprecated, import 'pandas.plotting.scatter_matrix' instead.\n",
" \"\"\"Entry point for launching an IPython kernel.\n"
]
},
{
"data": {
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8mWmMMHPwhFQeP96VVpsO99jJdenKUj742hW8bfsylpTkTurb6Q5InLFEW5Mi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\n8eHDhw8fPYb/D6ehI+K/KyaCAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fb505f5eba8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"scatter_matrix(dataframe)"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"_cell_guid": "dca8e347-c04c-4440-ac75-35d6b8dc8def",
"_uuid": "033bd0e40ed68085ab92426657340d8f666eaeab"
},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.text.Text at 0x7fb4f2058be0>,\n",
" <matplotlib.text.Text at 0x7fb4f2061550>,\n",
" <matplotlib.text.Text at 0x7fb4f1f77c18>,\n",
" <matplotlib.text.Text at 0x7fb4f218a780>,\n",
" <matplotlib.text.Text at 0x7fb4f215f240>,\n",
" <matplotlib.text.Text at 0x7fb4f215f4e0>,\n",
" <matplotlib.text.Text at 0x7fb4f1f26b70>,\n",
" <matplotlib.text.Text at 0x7fb4f2166dd8>,\n",
" <matplotlib.text.Text at 0x7fb4f1f37588>,\n",
" <matplotlib.text.Text at 0x7fb4f216cba8>,\n",
" <matplotlib.text.Text at 0x7fb4f1ec0c18>,\n",
" <matplotlib.text.Text at 0x7fb4f2173e80>,\n",
" <matplotlib.text.Text at 0x7fb4f217f0b8>,\n",
" <matplotlib.text.Text at 0x7fb4f2819f60>,\n",
" <matplotlib.text.Text at 0x7fb4f217ae10>]"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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gCILmo4brAdQVXTIAfU2e2cyWAj8EHvRrfbpyiCAImg2z5u0D6HIzRTPKM5vZ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\n9MZwAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fb4f208c780>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig = plt.figure()\n",
"ax = fig.add_subplot(111)\n",
"cax = ax.matshow(dataframe.corr(), vmin=-1, vmax=1)\n",
"fig.colorbar(cax)\n",
"ticks = numpy.arange(0,15,1)\n",
"ax.set_xticks(ticks)\n",
"ax.set_yticks(ticks)\n",
"ax.set_xticklabels(dataframe.columns)\n",
"ax.set_yticklabels(dataframe.columns)"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "87fe5b77-5127-4306-914f-88d28e4e5d78",
"_uuid": "8565a98c251af3e0c037a74933139d618691d47e"
},
"source": [
"'marital_status' has the highest positive corelation as expected"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "f1ce4fbd-c879-43b2-ac42-95ebea43aeb3",
"_uuid": "b7b70270645f229756a5329f5386aa1b26d444ab"
},
"source": [
"\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"**MACHINE LEARNING ESTIMATORS/MODELS**"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"_cell_guid": "f2cc9fda-5db7-418d-b7ba-80a4d065b603",
"_uuid": "479913229cfa2cfac34d3dbe6f5982edc34e2f75"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"X_Train: (21113, 14)\n",
"X_Test: (9049, 14)\n",
"Y_Train: (21113,)\n",
"Y_Test: (9049,)\n"
]
}
],
"source": [
"# Split Data to Train and Test\n",
"X_Train, X_Test, Y_Train, Y_Test = train_test_split(X, Y, test_size=0.3)\n",
"print(\"X_Train: \", X_Train.shape)\n",
"print(\"X_Test: \", X_Test.shape)\n",
"print(\"Y_Train: \", Y_Train.shape)\n",
"print(\"Y_Test: \", Y_Test.shape)"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"_cell_guid": "35fd3c27-a714-400b-b49f-a3ada8b4681a",
"_uuid": "a8e51608194ccc1a8a24c90a07720975ba411624"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"LR: 0.793900 (0.206100)\n",
"LDA: 0.825616 (0.174384)\n",
"KNN: 0.771687 (0.228313)\n",
"CART: 0.808929 (0.191071)\n",
"NB: 0.793237 (0.206763)\n",
"SVM: 0.755222 (0.244778)\n",
"L_SVM: 0.244778 (0.755222)\n",
"SGDC: 0.791027 (0.208973)\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/opt/conda/lib/python3.6/site-packages/sklearn/linear_model/stochastic_gradient.py:128: FutureWarning: max_iter and tol parameters have been added in <class 'sklearn.linear_model.stochastic_gradient.SGDClassifier'> in 0.19. If both are left unset, they default to max_iter=5 and tol=None. If tol is not None, max_iter defaults to max_iter=1000. From 0.21, default max_iter will be 1000, and default tol will be 1e-3.\n",
" \"and default tol will be 1e-3.\" % type(self), FutureWarning)\n"
]
}
],
"source": [
"\n",
"\n",
"num_instances = len(X)\n",
"\n",
"models = []\n",
"models.append(('LR', LogisticRegression()))\n",
"models.append(('LDA', LinearDiscriminantAnalysis()))\n",
"models.append(('KNN', KNeighborsClassifier()))\n",
"models.append(('CART', DecisionTreeClassifier()))\n",
"models.append(('NB', GaussianNB()))\n",
"models.append(('SVM', SVC()))\n",
"models.append(('L_SVM', LinearSVC()))\n",
"models.append(('SGDC', SGDClassifier()))\n",
"\n",
"# Evaluations\n",
"results = []\n",
"names = []\n",
"\n",
"for name, model in models:\n",
" # Fit the model\n",
" model.fit(X_Train, Y_Train)\n",
" \n",
" predictions = model.predict(X_Test)\n",
" \n",
" # Evaluate the model\n",
" score = accuracy_score(Y_Test, predictions)\n",
" mse = mean_squared_error(predictions, Y_Test)\n",
" # print(\"%s: %.2f%%\" % (model.metrics_names[1], scores[1]*100))\n",
" results.append(mse)\n",
" names.append(name)\n",
" \n",
" msg = \"%s: %f (%f)\" % (name, score, mse)\n",
" print(msg)\n",
" "
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "8dabb27e-1f90-454d-a0f9-bc4deb884a0c",
"_uuid": "3158587bf6939bc9882f5c8a5e8c1c067bccf0cc"
},
"source": [
"'Linear Discriminant Analysis' is the best estimators/models for this dataset, followed by 'LogisticRegression' and 'K Nearest Neighbour', they can be further explored and their hyperparameters tuned"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "c9ae367d-50e4-4005-8b79-83480b938ec2",
"_uuid": "6a66ba38426c61fcaa5931b3df03363c5c493696"
},
"source": [
"**DEEP LEARNING: MULTILAYER PERCEPTRON(ARTIFICIAL NEURAL NETWORK)**"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"_cell_guid": "7ac5180d-d731-45e7-82c5-ed62f2e8a20f",
"_uuid": "1204df79f94dad7f2ffe22759f50b1ab0297029e"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 1/300\n",
"21113/21113 [==============================] - 4s - loss: 0.5646 - acc: 0.7679 \n",
"Epoch 2/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5216 - acc: 0.7817 \n",
"Epoch 3/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5138 - acc: 0.7846 \n",
"Epoch 4/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5119 - acc: 0.7848 \n",
"Epoch 5/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5085 - acc: 0.7868 \n",
"Epoch 6/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5097 - acc: 0.7853 \n",
"Epoch 7/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5088 - acc: 0.7868 \n",
"Epoch 8/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5071 - acc: 0.7870 \n",
"Epoch 9/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5101 - acc: 0.7873 \n",
"Epoch 10/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5094 - acc: 0.7873 \n",
"Epoch 11/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5078 - acc: 0.7870 \n",
"Epoch 12/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5071 - acc: 0.7888 \n",
"Epoch 13/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5090 - acc: 0.7881 \n",
"Epoch 14/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5071 - acc: 0.7884 \n",
"Epoch 15/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5073 - acc: 0.7876 \n",
"Epoch 16/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5066 - acc: 0.7887 \n",
"Epoch 17/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5045 - acc: 0.7893 \n",
"Epoch 18/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5072 - acc: 0.7887 \n",
"Epoch 19/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5059 - acc: 0.7910 \n",
"Epoch 20/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5078 - acc: 0.7880 \n",
"Epoch 21/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5065 - acc: 0.7906 \n",
"Epoch 22/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5073 - acc: 0.7890 \n",
"Epoch 23/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5063 - acc: 0.7908 \n",
"Epoch 24/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5064 - acc: 0.7892 \n",
"Epoch 25/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5086 - acc: 0.7877 \n",
"Epoch 26/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5070 - acc: 0.7896 \n",
"Epoch 27/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5095 - acc: 0.7878 \n",
"Epoch 28/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5061 - acc: 0.7887 \n",
"Epoch 29/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5068 - acc: 0.7889 \n",
"Epoch 30/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5056 - acc: 0.7897 \n",
"Epoch 31/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5048 - acc: 0.7897 \n",
"Epoch 32/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5050 - acc: 0.7882 \n",
"Epoch 33/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5052 - acc: 0.7897 \n",
"Epoch 34/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5079 - acc: 0.7872 \n",
"Epoch 35/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5071 - acc: 0.7894 \n",
"Epoch 36/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5036 - acc: 0.7896 \n",
"Epoch 37/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5057 - acc: 0.7883 \n",
"Epoch 38/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5050 - acc: 0.7880 \n",
"Epoch 39/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5045 - acc: 0.7907 \n",
"Epoch 40/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5057 - acc: 0.7894 \n",
"Epoch 41/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5099 - acc: 0.7861 \n",
"Epoch 42/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5048 - acc: 0.7898 \n",
"Epoch 43/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5064 - acc: 0.7888 \n",
"Epoch 44/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5056 - acc: 0.7889 \n",
"Epoch 45/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5050 - acc: 0.7909 \n",
"Epoch 46/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5046 - acc: 0.7907 \n",
"Epoch 47/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5043 - acc: 0.7909 \n",
"Epoch 48/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5053 - acc: 0.7907 \n",
"Epoch 49/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5045 - acc: 0.7899 \n",
"Epoch 50/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5043 - acc: 0.7898 \n",
"Epoch 51/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5043 - acc: 0.7906 \n",
"Epoch 52/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5044 - acc: 0.7908 \n",
"Epoch 53/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5065 - acc: 0.7891 \n",
"Epoch 54/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5045 - acc: 0.7899 \n",
"Epoch 55/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5043 - acc: 0.7922 \n",
"Epoch 56/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5041 - acc: 0.7909 \n",
"Epoch 57/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5054 - acc: 0.7884 \n",
"Epoch 58/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5040 - acc: 0.7906 \n",
"Epoch 59/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5036 - acc: 0.7902 \n",
"Epoch 60/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5049 - acc: 0.7914 \n",
"Epoch 61/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5049 - acc: 0.7903 \n",
"Epoch 62/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5046 - acc: 0.7898 \n",
"Epoch 63/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5037 - acc: 0.7908 \n",
"Epoch 64/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5044 - acc: 0.7907 \n",
"Epoch 65/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5051 - acc: 0.7900 \n",
"Epoch 66/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5038 - acc: 0.7897 \n",
"Epoch 67/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5043 - acc: 0.7899 \n",
"Epoch 68/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5047 - acc: 0.7899 \n",
"Epoch 69/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5037 - acc: 0.7905 \n",
"Epoch 70/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5073 - acc: 0.7898 \n",
"Epoch 71/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5060 - acc: 0.7889 \n",
"Epoch 72/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5056 - acc: 0.7905 \n",
"Epoch 73/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5037 - acc: 0.7904 \n",
"Epoch 74/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5203 - acc: 0.7817 \n",
"Epoch 75/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5063 - acc: 0.7878 \n",
"Epoch 76/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5040 - acc: 0.7907 \n",
"Epoch 77/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5036 - acc: 0.7894 \n",
"Epoch 78/300\n",
"21113/21113 [==============================] - 4s - loss: 0.5052 - acc: 0.7901 \n",
"Epoch 79/300\n",
"21113/21113 [==============================] - 4s - loss: 0.5031 - acc: 0.7923 \n",
"Epoch 80/300\n",
"21113/21113 [==============================] - 4s - loss: 0.5044 - acc: 0.7897 \n",
"Epoch 81/300\n",
"21113/21113 [==============================] - 4s - loss: 0.5026 - acc: 0.7921 \n",
"Epoch 82/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5032 - acc: 0.7903 \n",
"Epoch 83/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5042 - acc: 0.7909 \n",
"Epoch 84/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5044 - acc: 0.7901 \n",
"Epoch 85/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5061 - acc: 0.7898 \n",
"Epoch 86/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5055 - acc: 0.7898 \n",
"Epoch 87/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5015 - acc: 0.7924 \n",
"Epoch 88/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5053 - acc: 0.7901 \n",
"Epoch 89/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5026 - acc: 0.7913 \n",
"Epoch 90/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5047 - acc: 0.7900 \n",
"Epoch 91/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5047 - acc: 0.7904 \n",
"Epoch 92/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5049 - acc: 0.7899 \n",
"Epoch 93/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5033 - acc: 0.7915 \n",
"Epoch 94/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5020 - acc: 0.7932 \n",
"Epoch 95/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5031 - acc: 0.7915 \n",
"Epoch 96/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5086 - acc: 0.7860 \n",
"Epoch 97/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5043 - acc: 0.7901 \n",
"Epoch 98/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5041 - acc: 0.7898 \n",
"Epoch 99/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5092 - acc: 0.7867 \n",
"Epoch 100/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5045 - acc: 0.7907 \n",
"Epoch 101/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5033 - acc: 0.7913 \n",
"Epoch 102/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5065 - acc: 0.7888 \n",
"Epoch 103/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5051 - acc: 0.7904 \n",
"Epoch 104/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5043 - acc: 0.7899 \n",
"Epoch 105/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5041 - acc: 0.7890 \n",
"Epoch 106/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5086 - acc: 0.7873 \n",
"Epoch 107/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5131 - acc: 0.7852 \n",
"Epoch 108/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5080 - acc: 0.7884 \n",
"Epoch 109/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5040 - acc: 0.7921 \n",
"Epoch 110/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5025 - acc: 0.7907 \n",
"Epoch 111/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5048 - acc: 0.7895 \n",
"Epoch 112/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5031 - acc: 0.7912 \n",
"Epoch 113/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5037 - acc: 0.7905 \n",
"Epoch 114/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5041 - acc: 0.7890 \n",
"Epoch 115/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5001 - acc: 0.7936 \n",
"Epoch 116/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5036 - acc: 0.7903 \n",
"Epoch 117/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5048 - acc: 0.7907 \n",
"Epoch 118/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5024 - acc: 0.7905 \n",
"Epoch 119/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5074 - acc: 0.7881 \n",
"Epoch 120/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5030 - acc: 0.7905 \n",
"Epoch 121/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5032 - acc: 0.7917 \n",
"Epoch 122/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5037 - acc: 0.7906 \n",
"Epoch 123/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5042 - acc: 0.7894 \n",
"Epoch 124/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5026 - acc: 0.7925 \n",
"Epoch 125/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5012 - acc: 0.7919 \n",
"Epoch 126/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5046 - acc: 0.7892 \n",
"Epoch 127/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5115 - acc: 0.7862 \n",
"Epoch 128/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5073 - acc: 0.7890 \n",
"Epoch 129/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5058 - acc: 0.7891 \n",
"Epoch 130/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5035 - acc: 0.7913 \n",
"Epoch 131/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5040 - acc: 0.7913 \n",
"Epoch 132/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5033 - acc: 0.7917 \n",
"Epoch 133/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5011 - acc: 0.7916 \n",
"Epoch 134/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5015 - acc: 0.7915 \n",
"Epoch 135/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5030 - acc: 0.7909 \n",
"Epoch 136/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5014 - acc: 0.7915 \n",
"Epoch 137/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5030 - acc: 0.7916 \n",
"Epoch 138/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5002 - acc: 0.7929 \n",
"Epoch 139/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5044 - acc: 0.7898 \n",
"Epoch 140/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5031 - acc: 0.7915 \n",
"Epoch 141/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5019 - acc: 0.7930 \n",
"Epoch 142/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5039 - acc: 0.7905 \n",
"Epoch 143/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5018 - acc: 0.7925 \n",
"Epoch 144/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5004 - acc: 0.7942 \n",
"Epoch 145/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5031 - acc: 0.7916 \n",
"Epoch 146/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5046 - acc: 0.7903 \n",
"Epoch 147/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5025 - acc: 0.7920 \n",
"Epoch 148/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5025 - acc: 0.7916 \n",
"Epoch 149/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5021 - acc: 0.7908 \n",
"Epoch 150/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5023 - acc: 0.7934 \n",
"Epoch 151/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5013 - acc: 0.7936 \n",
"Epoch 152/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5019 - acc: 0.7931 \n",
"Epoch 153/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5007 - acc: 0.7929 \n",
"Epoch 154/300\n",
"21113/21113 [==============================] - 3s - loss: 0.5038 - acc: 0.7913 \n",
"Epoch 155/300\n",
"13460/21113 [==================>...........] - ETA: 1s - loss: 0.4989 - acc: 0.7952"
]
}
],
"source": [
"# create model\n",
"model = Sequential()\n",
"model.add(Dense(28, input_dim=14, activation='relu', kernel_initializer=\"uniform\"))\n",
"model.add(Dropout(0.2))\n",
"model.add(Dense(20, activation='relu', kernel_constraint=maxnorm(3), kernel_initializer=\"uniform\"))\n",
"model.add(Dropout(0.2))\n",
"model.add(Dense(10, activation='relu', kernel_initializer=\"uniform\"))\n",
"model.add(Dense(1, activation='sigmoid', kernel_initializer=\"uniform\"))\n",
"\n",
"# Compile model\n",
"model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])\n",
"\n",
"# Fit the model\n",
"model.fit(X_Train, Y_Train, epochs=300, batch_size=10)\n",
"\n",
"# Evaluate the model\n",
"scores = model.evaluate(X_Test, Y_Test)\n",
"print(\"%s: %.2f%%\" % (model.metrics_names[1], scores[1]*100))"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.1"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
| 0001/479/1479739.ipynb | s3://data-agents/kaggle-outputs/sharded/034_00001.jsonl.gz |
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"According to US Census Bureau, population of Baltimore was estimated to drop to 614,664 in 2016 \n",
"from the 2010 figure of 621,195 which is approximately 0.18% decrease annually."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"_cell_guid": "519a801a-6a11-4631-9531-8bc4cbd711d0",
"_uuid": "5fd205aebc46710db845678b44bc798ac1ff539f",
"collapsed": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"911_calls_for_service.csv\n",
"\n"
]
}
],
"source": [
"# This Python 3 environment comes with many helpful analytics libraries installed\n",
"# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n",
"# For example, here's several helpful packages to load in \n",
"\n",
"import numpy as np # linear algebra\n",
"import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
"\n",
"# Input data files are available in the \"../input/\" directory.\n",
"# For example, running this (by clicking run or pressing Shift+Enter) will list the files in the input directory\n",
"\n",
"from subprocess import check_output\n",
"print(check_output([\"ls\", \"../input\"]).decode(\"utf8\"))\n",
"\n",
"# Any results you write to the current directory are saved as output."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"from scipy.stats import ttest_ind as ttest\n",
"import matplotlib.pyplot as plt\n",
"import pandas as pd\n",
"import numpy as np"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# This function counts the number of calls\n",
"# @param pandas Series of calls\n",
"# @param desired year\n",
"# @return pandas Series of call count per month\n",
"def count_it(calls, yr, prty='All' , weekly=True):\n",
" if prty == 'All':\n",
" call_list = calls\n",
" else:\n",
" call_list = calls[calls['priority']==prty]\n",
"\n",
" date_series = pd.to_datetime(call_list['callDateTime'])\n",
"\n",
" if weekly:\n",
" date_series = date_series[date_series.dt.year == yr]\n",
" return date_series.dt.week.value_counts()\n",
"\n",
" if yr == 2017: mths = 7\n",
" else: mths = 12\n",
"\n",
" counts = pd.Series(np.zeros(mths), index=range(1,mths+1))\n",
"\n",
" for mth in xrange(1,mths+1):\n",
" counts.set_value(label = mth, value = date_series[(date_series.dt.year == yr) &\n",
" (date_series.dt.month == mth)].count())\n",
"\n",
" return counts"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# This function calculates the median number of calls per week\n",
"# @param pandas Series of calls\n",
"# @param desired priority or all calls\n",
"# @return pandas Series of median number of calls per week\n",
"def weekly_medians(calls,prty):\n",
" if prty == 'All':\n",
" call_list = calls\n",
" else:\n",
" call_list = calls[calls['priority']==prty]\n",
"\n",
" return pd.Series([count_it(call_list, 2015).median(),\n",
" count_it(call_list, 2016).median(),\n",
" count_it(call_list, 2017).median()],\n",
" index=[2015,2016,2017],\n",
" name=prty)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# This function runs ttest on weekly number of calls\n",
"# @param pandas Series of calls\n",
"# @param desired year\n",
"# @return pandas Series of call count per month\n",
"def run_ttest(calls, prty):\n",
" if prty == 'All':\n",
" call_list = calls\n",
" else:\n",
" call_list = calls[calls['priority']==prty]\n",
"\n",
" return pd.Series([ttest(count_it(call_list,2015),count_it(call_list,2016))[1],\n",
" ttest(count_it(call_list, 2016), count_it(call_list, 2017))[1]],\n",
" index=[2016,2017],\n",
" name=prty)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/opt/conda/lib/python3.6/site-packages/numpy/lib/arraysetops.py:463: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
" mask |= (ar1 == a)\n"
]
}
],
"source": [
"# Load dataset into the memory\n",
"all_calls = pd.DataFrame(pd.read_csv('../input/911_calls_for_service.csv',index_col=0))"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.1"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
| 0001/479/1479740.ipynb | s3://data-agents/kaggle-outputs/sharded/034_00001.jsonl.gz |
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"_cell_guid": "92192430-a832-4c21-8de7-a9937ee30259",
"_uuid": "b514f9009e5f1e2ab2942a3d429f14967af4a120"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"diabetes.csv\n",
"\n"
]
}
],
"source": [
"# This Python 3 environment comes with many helpful analytics libraries installed\n",
"# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n",
"# For example, here's several helpful packages to load in \n",
"\n",
"import numpy as np # linear algebra\n",
"import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
"\n",
"# Input data files are available in the \"../input/\" directory.\n",
"# For example, running this (by clicking run or pressing Shift+Enter) will list the files in the input directory\n",
"\n",
"from subprocess import check_output\n",
"print(check_output([\"ls\", \"../input\"]).decode(\"utf8\"))\n",
"\n",
"# Any results you write to the current directory are saved as output."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"_cell_guid": "9f4d8585-d142-4151-b2cf-a48ff7ce0c1d",
"_uuid": "018ec3715785dfb39e4a79ee2673721d75232745",
"collapsed": true
},
"outputs": [],
"source": [
"#IMPORTING THE BASIC LIBRARIES\n",
"import numpy as np # linear algebra\n",
"import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
"import os\n",
"import gc\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"#matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"_cell_guid": "cda84805-a8a0-41b0-b339-4a6f4ae18f19",
"_uuid": "8cdf2f38cde6d9fc58cbcb48bbf34c8867dd8ee5"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"File Sizes:\n",
"diabetes.csv 23.87 KB\n"
]
}
],
"source": [
"INPUT_FOLDER= \"../input/\"\n",
"print ('File Sizes:')\n",
"for f in os.listdir(INPUT_FOLDER):\n",
" if 'zip' not in f:\n",
" print (f.ljust(30) + str(round(os.path.getsize(INPUT_FOLDER + f) / 1000, 2)) + ' KB')"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"_cell_guid": "1b5637ed-c440-430e-bd01-eb942ef14b57",
"_uuid": "4fe766d5a44dafd1fd4189f23276fa2c6e8ad1d1"
},
"outputs": [
{
"data": {
"text/plain": [
"(768, 9)"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#CREATING A DATAFRAME FOR THE MAIN FILE TO BE USED IN THE CODE\n",
"main_file=pd.read_csv(INPUT_FOLDER + 'diabetes.csv')\n",
"main_file.shape"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"_cell_guid": "13877a95-c2b3-40f4-86e5-4de0812e3fd3",
"_uuid": "5abc76db3dfcaaaa658bbe55566d8b2f57ad7a8f"
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Pregnancies</th>\n",
" <th>Glucose</th>\n",
" <th>BloodPressure</th>\n",
" <th>SkinThickness</th>\n",
" <th>Insulin</th>\n",
" <th>BMI</th>\n",
" <th>DiabetesPedigreeFunction</th>\n",
" <th>Age</th>\n",
" <th>Outcome</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>768.000000</td>\n",
" <td>768.000000</td>\n",
" <td>768.000000</td>\n",
" <td>768.000000</td>\n",
" <td>768.000000</td>\n",
" <td>768.000000</td>\n",
" <td>768.000000</td>\n",
" <td>768.000000</td>\n",
" <td>768.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>3.845052</td>\n",
" <td>120.894531</td>\n",
" <td>69.105469</td>\n",
" <td>20.536458</td>\n",
" <td>79.799479</td>\n",
" <td>31.992578</td>\n",
" <td>0.471876</td>\n",
" <td>33.240885</td>\n",
" <td>0.348958</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>3.369578</td>\n",
" <td>31.972618</td>\n",
" <td>19.355807</td>\n",
" <td>15.952218</td>\n",
" <td>115.244002</td>\n",
" <td>7.884160</td>\n",
" <td>0.331329</td>\n",
" <td>11.760232</td>\n",
" <td>0.476951</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.078000</td>\n",
" <td>21.000000</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>1.000000</td>\n",
" <td>99.000000</td>\n",
" <td>62.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>27.300000</td>\n",
" <td>0.243750</td>\n",
" <td>24.000000</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>3.000000</td>\n",
" <td>117.000000</td>\n",
" <td>72.000000</td>\n",
" <td>23.000000</td>\n",
" <td>30.500000</td>\n",
" <td>32.000000</td>\n",
" <td>0.372500</td>\n",
" <td>29.000000</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>6.000000</td>\n",
" <td>140.250000</td>\n",
" <td>80.000000</td>\n",
" <td>32.000000</td>\n",
" <td>127.250000</td>\n",
" <td>36.600000</td>\n",
" <td>0.626250</td>\n",
" <td>41.000000</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>max</th>\n",
" <td>17.000000</td>\n",
" <td>199.000000</td>\n",
" <td>122.000000</td>\n",
" <td>99.000000</td>\n",
" <td>846.000000</td>\n",
" <td>67.100000</td>\n",
" <td>2.420000</td>\n",
" <td>81.000000</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Pregnancies Glucose BloodPressure SkinThickness Insulin \\\n",
"count 768.000000 768.000000 768.000000 768.000000 768.000000 \n",
"mean 3.845052 120.894531 69.105469 20.536458 79.799479 \n",
"std 3.369578 31.972618 19.355807 15.952218 115.244002 \n",
"min 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"25% 1.000000 99.000000 62.000000 0.000000 0.000000 \n",
"50% 3.000000 117.000000 72.000000 23.000000 30.500000 \n",
"75% 6.000000 140.250000 80.000000 32.000000 127.250000 \n",
"max 17.000000 199.000000 122.000000 99.000000 846.000000 \n",
"\n",
" BMI DiabetesPedigreeFunction Age Outcome \n",
"count 768.000000 768.000000 768.000000 768.000000 \n",
"mean 31.992578 0.471876 33.240885 0.348958 \n",
"std 7.884160 0.331329 11.760232 0.476951 \n",
"min 0.000000 0.078000 21.000000 0.000000 \n",
"25% 27.300000 0.243750 24.000000 0.000000 \n",
"50% 32.000000 0.372500 29.000000 0.000000 \n",
"75% 36.600000 0.626250 41.000000 1.000000 \n",
"max 67.100000 2.420000 81.000000 1.000000 "
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"main_file.describe()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"_cell_guid": "0ecd7a4e-772f-4d13-bedd-c4887c77f0f5",
"_uuid": "8d24b27f56da027ef2d7f412ee2737f7718afc1d"
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
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" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Pregnancies</th>\n",
" <th>Glucose</th>\n",
" <th>BloodPressure</th>\n",
" <th>SkinThickness</th>\n",
" <th>Insulin</th>\n",
" <th>BMI</th>\n",
" <th>DiabetesPedigreeFunction</th>\n",
" <th>Age</th>\n",
" <th>Outcome</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>6</td>\n",
" <td>148</td>\n",
" <td>72</td>\n",
" <td>35</td>\n",
" <td>0</td>\n",
" <td>33.6</td>\n",
" <td>0.627</td>\n",
" <td>50</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>1</td>\n",
" <td>85</td>\n",
" <td>66</td>\n",
" <td>29</td>\n",
" <td>0</td>\n",
" <td>26.6</td>\n",
" <td>0.351</td>\n",
" <td>31</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>8</td>\n",
" <td>183</td>\n",
" <td>64</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>23.3</td>\n",
" <td>0.672</td>\n",
" <td>32</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>1</td>\n",
" <td>89</td>\n",
" <td>66</td>\n",
" <td>23</td>\n",
" <td>94</td>\n",
" <td>28.1</td>\n",
" <td>0.167</td>\n",
" <td>21</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>0</td>\n",
" <td>137</td>\n",
" <td>40</td>\n",
" <td>35</td>\n",
" <td>168</td>\n",
" <td>43.1</td>\n",
" <td>2.288</td>\n",
" <td>33</td>\n",
" <td>1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Pregnancies Glucose BloodPressure SkinThickness Insulin BMI \\\n",
"0 6 148 72 35 0 33.6 \n",
"1 1 85 66 29 0 26.6 \n",
"2 8 183 64 0 0 23.3 \n",
"3 1 89 66 23 94 28.1 \n",
"4 0 137 40 35 168 43.1 \n",
"\n",
" DiabetesPedigreeFunction Age Outcome \n",
"0 0.627 50 1 \n",
"1 0.351 31 0 \n",
"2 0.672 32 1 \n",
"3 0.167 21 0 \n",
"4 2.288 33 1 "
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"main_file.head()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"_cell_guid": "ffd17f35-435a-4065-9aec-12abb7409478",
"_uuid": "a0c04a0872dc0de0d041509e151f03634248e9ee"
},
"outputs": [
{
"data": {
"text/plain": [
"Outcome\n",
"0 500\n",
"1 268\n",
"dtype: int64"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#COUNTING THE PEOPLE WITH AND WITHOUT DIABETES\n",
"main_file.groupby(\"Outcome\").size()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"_cell_guid": "02a99044-816d-4fa1-809b-fe923d492167",
"_uuid": "3320c2dba2fce7eebc01b458568508e95ba74158"
},
"outputs": [
{
"data": {
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irKyM7Oxsli1bBkBkZCQpKSnce++9hIeHExQUBMCAAQPIyckhKirKbbGL3ColVyItpCty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\nQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f452dddba58>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"<matplotlib.figure.Figure at 0x7f452db54b38>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"main_file.hist(figsize=(10,8))\n",
"plt.figure()\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "25f7f889-fa5e-4f5e-8d77-939573f96252",
"_uuid": "97a29eef7ff8cd2798b628624a5132a73857c850"
},
"source": [
"**Replacing '0' values of the columns mentioned below with their respective column mode.\n",
"** \n",
"* BMI\n",
"* BLOOD PRESSURE\n",
"* GLUCOSE"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"_cell_guid": "d0457c0c-b2c6-4f06-b48e-44a4782188b1",
"_uuid": "4e35ee1adfab8544422e976484e936dfad273125",
"collapsed": true
},
"outputs": [],
"source": [
"bmi_mode=main_file[\"BMI\"].mode()"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"_cell_guid": "2720e2e9-f180-4dcc-a993-27a6e2430ac6",
"_uuid": "48184840553a0aca66a285a87b3d3783c38a1782"
},
"outputs": [
{
"data": {
"text/plain": [
"0 32.0\n",
"dtype: float64"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"bmi_mode"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"_cell_guid": "576decda-ea6c-4236-9393-34caf95d5de4",
"_uuid": "a48db101072f8622b36fe076fdffa495a5192c50",
"collapsed": true
},
"outputs": [],
"source": [
"main_file=main_file.replace({'BMI': {0: 32}}) "
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"_cell_guid": "fb3a4b2c-a6ae-4d56-82d5-92a6f92646ba",
"_uuid": "8300b08acf996c63064e78ebd806d5288d751004"
},
"outputs": [
{
"data": {
"text/plain": [
"0 70\n",
"dtype: int64"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"bp_mode=main_file[\"BloodPressure\"].mode()\n",
"bp_mode"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"_cell_guid": "d5c823ed-3239-4a29-b9ed-b0dc1df8031d",
"_uuid": "285ad6fe7c235edcadcf01ca61d819df8bceed6d",
"collapsed": true
},
"outputs": [],
"source": [
"main_file=main_file.replace({'BloodPressure': {0: 70}}) "
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"_cell_guid": "9b6d97b0-f3e7-476b-8e21-9953352e9de9",
"_uuid": "c15db477a15af525698e72e81256c46b9d7e3a3d"
},
"outputs": [
{
"data": {
"text/plain": [
"0 99\n",
"1 100\n",
"dtype: int64"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"glu_mode=main_file[\"Glucose\"].mode()\n",
"glu_mode"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"_cell_guid": "3eca47b9-7218-4d78-bc98-dca15322bc36",
"_uuid": "4ecb6698ea7dc2deb004404426d92bfb4b7b2b52",
"collapsed": true
},
"outputs": [],
"source": [
"main_file=main_file.replace({'Glucose': {0: 99.5}}) "
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"_cell_guid": "b53ef1db-4467-49d0-90b9-e8bd751510e2",
"_uuid": "375c9beb8b12d8e1a68a15845877f58a6097468f"
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Pregnancies</th>\n",
" <th>Glucose</th>\n",
" <th>BloodPressure</th>\n",
" <th>SkinThickness</th>\n",
" <th>Insulin</th>\n",
" <th>BMI</th>\n",
" <th>DiabetesPedigreeFunction</th>\n",
" <th>Age</th>\n",
" <th>Outcome</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>768.000000</td>\n",
" <td>768.000000</td>\n",
" <td>768.000000</td>\n",
" <td>768.000000</td>\n",
" <td>768.000000</td>\n",
" <td>768.000000</td>\n",
" <td>768.000000</td>\n",
" <td>768.000000</td>\n",
" <td>768.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>3.845052</td>\n",
" <td>121.542318</td>\n",
" <td>72.295573</td>\n",
" <td>20.536458</td>\n",
" <td>79.799479</td>\n",
" <td>32.450911</td>\n",
" <td>0.471876</td>\n",
" <td>33.240885</td>\n",
" <td>0.348958</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>3.369578</td>\n",
" <td>30.488277</td>\n",
" <td>12.106756</td>\n",
" <td>15.952218</td>\n",
" <td>115.244002</td>\n",
" <td>6.875366</td>\n",
" <td>0.331329</td>\n",
" <td>11.760232</td>\n",
" <td>0.476951</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>0.000000</td>\n",
" <td>44.000000</td>\n",
" <td>24.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>18.200000</td>\n",
" <td>0.078000</td>\n",
" <td>21.000000</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>1.000000</td>\n",
" <td>99.375000</td>\n",
" <td>64.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>27.500000</td>\n",
" <td>0.243750</td>\n",
" <td>24.000000</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>3.000000</td>\n",
" <td>117.000000</td>\n",
" <td>72.000000</td>\n",
" <td>23.000000</td>\n",
" <td>30.500000</td>\n",
" <td>32.000000</td>\n",
" <td>0.372500</td>\n",
" <td>29.000000</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>6.000000</td>\n",
" <td>140.250000</td>\n",
" <td>80.000000</td>\n",
" <td>32.000000</td>\n",
" <td>127.250000</td>\n",
" <td>36.600000</td>\n",
" <td>0.626250</td>\n",
" <td>41.000000</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>max</th>\n",
" <td>17.000000</td>\n",
" <td>199.000000</td>\n",
" <td>122.000000</td>\n",
" <td>99.000000</td>\n",
" <td>846.000000</td>\n",
" <td>67.100000</td>\n",
" <td>2.420000</td>\n",
" <td>81.000000</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Pregnancies Glucose BloodPressure SkinThickness Insulin \\\n",
"count 768.000000 768.000000 768.000000 768.000000 768.000000 \n",
"mean 3.845052 121.542318 72.295573 20.536458 79.799479 \n",
"std 3.369578 30.488277 12.106756 15.952218 115.244002 \n",
"min 0.000000 44.000000 24.000000 0.000000 0.000000 \n",
"25% 1.000000 99.375000 64.000000 0.000000 0.000000 \n",
"50% 3.000000 117.000000 72.000000 23.000000 30.500000 \n",
"75% 6.000000 140.250000 80.000000 32.000000 127.250000 \n",
"max 17.000000 199.000000 122.000000 99.000000 846.000000 \n",
"\n",
" BMI DiabetesPedigreeFunction Age Outcome \n",
"count 768.000000 768.000000 768.000000 768.000000 \n",
"mean 32.450911 0.471876 33.240885 0.348958 \n",
"std 6.875366 0.331329 11.760232 0.476951 \n",
"min 18.200000 0.078000 21.000000 0.000000 \n",
"25% 27.500000 0.243750 24.000000 0.000000 \n",
"50% 32.000000 0.372500 29.000000 0.000000 \n",
"75% 36.600000 0.626250 41.000000 1.000000 \n",
"max 67.100000 2.420000 81.000000 1.000000 "
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"main_file.describe()"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"_cell_guid": "64669065-294a-4dcd-93a9-1cbae267e114",
"_uuid": "7c4c32f7d7813f28d7e45819791b26977706125c"
},
"outputs": [
{
"data": {
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Ae3t7TJ06FVOmTLF06ETNwiSLiIgkd+nSJdy8eRNJSUnIy8vDhAkT4O3tjeDgYPj7+2PL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\nTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f452a0abc50>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"<matplotlib.figure.Figure at 0x7f452a3c6e48>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"main_file.hist(figsize=(10,8))\n",
"plt.figure()\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"_cell_guid": "0d34dcba-a275-4f1b-8b14-ca2b2b4763d1",
"_uuid": "187370a2edce3758d80ff2101e3aef7fb86a6784"
},
"outputs": [
{
"data": {
"text/plain": [
"Pregnancies Axes(0.125,0.657941;0.227941x0.222059)\n",
"Glucose Axes(0.398529,0.657941;0.227941x0.222059)\n",
"BloodPressure Axes(0.672059,0.657941;0.227941x0.222059)\n",
"SkinThickness Axes(0.125,0.391471;0.227941x0.222059)\n",
"Insulin Axes(0.398529,0.391471;0.227941x0.222059)\n",
"BMI Axes(0.672059,0.391471;0.227941x0.222059)\n",
"DiabetesPedigreeFunction Axes(0.125,0.125;0.227941x0.222059)\n",
"Age Axes(0.398529,0.125;0.227941x0.222059)\n",
"Outcome Axes(0.672059,0.125;0.227941x0.222059)\n",
"dtype: object"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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W/RQ4nSbTi3QkQKlmJlTSMGTmeRRrWjbaaOmlzFwILByRoKTR56bMPKTvRUR8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\nrpKplryrPgAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f4546d5bf60>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%matplotlib inline\n",
"main_file.plot(kind= 'box' , subplots=True, layout=(3,3), sharex=False, sharey=False, figsize=(10,8))"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"_cell_guid": "3dda37a8-de1e-4461-8ff1-baad334f8295",
"_uuid": "77510ae71941ea71fa142786574c9132abda7d67"
},
"outputs": [
{
"data": {
"text/plain": [
"<seaborn.axisgrid.PairGrid at 0x7f4529e84518>"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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LMB+9o/3ITEkPKhNrt4HHWS6VYGZunsedtpRY+6JYxi6xZT0qi79PnfV4MTM3H/T44r0L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\ncO8HgImizYhvuTm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Xm2+ILR/t6+Ycd+345lOzHi+SZUn+udX4lAf5klLB9z9fUoI5zwJO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cItYvkQXosLs8ZIKp/FpDGQzm4xYB7i6tUi4aUMAZeZoe421llkaWeaYHoBv9mHy2znUuwqPdZu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1Uc7w+HfsbLI29Wi6LuIthNaqb9kbLjDpP6UxhNFZ80murtgvud5g0oWd2v+NiSP1KpFKm0\n/Pb/8A//wN/93d/R0NDAH//xHxMMBtHr9cW/6/V6AgHhataPgkLSYS0KSYfm1gxeXMRTS4TicxiU\noLS6sKHlQGN+oTjrvoRr0YuzzsZ+R09RM1SIgp9IZXj3ohudpoYoIiRSGa2aJpaXRCAWoVTXAPlN\n6b95bjsXRvy4/VF2dZrYvcXM5sYGNtkDNHVE8a5IZ/TusGCTtCGJaQGIJGOCi/XCcpg6haaipjBA\nS30z706dKmPgPNR0GFhfum092Z+/ufg9wedccCRbdS2CP9I2XYvgdVVUUUUVdxIblS0bnpznyMFa\nsnVuToY+oEvfhVHdwID/CnqZDVnYwfkPkvR0mJDXLXIq9lLZZvtI015OTp3nWMtBYskl3GEfrfpm\nDjh244n4BOdoo1JH7eYcJoeSpHqKYNrHZNRJu3oHeqOeodAwM9FAsdq4ALFIjE5Rx99c+CfBebuK\nD4dx9yJbdsiQL0tXZPWk1CpkXBtd/Ej3/TCyeSf7PZy5Mk+dqY0vdjYyGXahlNZwYirfl2W/o1fQ\nhrRyNSpZfhPsUDtwycXkZEsopDXstHQV2cJbjR001OpI1acqMtGGAmOMhyZpbWi+eewWlfdVfLrQ\nVvD/tDU37aKAtVWw2yztuGaeZrnOxWLaj0lt4HWB3mRPtB/DobWWBVl0iroiw7yAQsJyNhbim2/8\nKVsMrei1NYhD4rJ5zJ9w09HYQ0cnxbnMVutk7x4rp84uk83mqJFJ0GlrODXguW27KxRenTq7fDN4\nmfLQod+UT8Qa28AI8DXOe/pwRadwqpvYa++t9vv5FFFpv3Wiz11iC6urqH/v/z3B6dkI+x+1My3Q\n73SvfSc/ufbyTRuPeJFLZHz5K0/x/vQZGvXbGV4U7l0BVEycT8aHuRYwcnLqPKOhGzyz+VFmIgGm\nFl3YtRY0chWBRRePPNjOrGSSuQpzcKFivbCPqiRl+ECPgy3GBrYY2xgJjPH69XcZnB1li6GtWIyS\nzWWrjItPEDt2Spivm6WhTkEkEeWD0Cy9pp3Y1FaGA6MYVDIebXuQWCJGKL5AOptekfIV0aJz3rJn\nCuSlA483/RKDc8MElBdISgwV+0vJJTLMagNeqRj/XFyQ+Zjv5dZzS1+yYIeFHoU6rRP/Uornfq29\n5Lz7RSr4s4xKyb5gysPn9+5mIZogMpvmkOM5lpUuPPFp7MpGWuqdjIWvI5PI2GnZRqeuE+/iDDWb\n/cyL6vjuG0FEcR0P9DjY2tLGGVcfrkVvMeYEoFPoy3yGAsok5ZIezPpmDuywcdl7nVc8PxT0TYYC\no2W/m1ZdC891PlZmd2emL3LWfQkRIrpMHWjkauKpZQ44exgKjJHKpErGm8xk72hRVNWf/mjY3KSj\nb2S2bD3sWFVAVMW9i6Z6O+c9/WW/98Z62zpX3d/4WHv+rMXx48epr6+ns7OTv/7rv+Yv//Iv6enp\nKTknl8vd8j7f/va3+cu//MsP9d4tdc2CSYeW+mYAMsoAF8YGyhaRJ9tMACwl08jFMlr1TZDLvy5g\n8Ea5Hj/A4MQcTzysYXRpOp+USaSQSWXIzdM4FXlZu5P9Hv77S1dKGpVdHJ6lViFFaQry/dGX14zp\nKr/c8QJQWdrDtehln6NHkNkjEYkBONa6n9Pu8/nqdaWOWCofDHiodV85/VdAG74SPfVW9O7C+wpV\nPd8PuB3braKKuwH3ku0KzV+rHfDutgYO7K/hNd+PSYZKA0L7lc/y7ltxEqkldm/RcG5whq4HfMKb\n7XSSX93xLEOzY4yExjjSuI+T0+eYWnSRyWbotW7P33ulaapOUccbYyeQiiUcadrHWxP5inRPxEt/\nsI/H7c8SiIfoMm0uC7rute/kxNTZdeft+xW3Y7vbe5J8b/QHa9aqS3yp56P3JNyIvMPJfg9/8b1L\nJFIZjhys5eTwT7GrLRg1DcUxrWaTBWNzmNVG5BI52VyWWCqOXCLDWq9HtOsGrugcn990hDfHyxtI\n77P3IBXLiq8LVZzJTAqDSsefvfdt/uDw19libNtQ5X0Vdw63Y7tmlVGwt6JR2VCszgXh6uutLQ2E\nFrfywVADdVIRnvBZwbnNHfbxkOMYV2dHUMmURXuJpeJsq+sqmZ/WMiOmFz0lleirYVc6WU4G+buh\nV8rOP3zgaXK5HCnNNMG0j7kaOyMB5W3Nb2vl4Ha07eaFXc/R7iwNGBxq3VZN9twmPg6fQUjyDCjK\nBAqhw1nPmGuBTNBRlN0qQC1X4o4IM9VGQqO06By8Nv5z9jt6EYskTC24MKsNNNU7eG30rXUlXP1J\nN//9wj8W59WTU2dJZVM80X6MqQU3b02cIpvLopYPslOzA7GIdSvWjzTtBW7d52rtHm4186PPd6XK\nuNgA7oTtjgTG+O6lv6bXup2Ta3wzfW0dT3Y8zPXQFHKRDLFCzXuj50q+s5HgGM9vfYIbcy484Rls\nWgtiESU9UwCa6py8Ov1jltMJOg1tJDLLZUkjyAfSO43tdOibefoL23n3ohtRVl3GfNzv6OWlVQ20\nK/mSt7LD1fg4Ja2qwfNS3I7tVordNMjsxBdSfDDkz/t8w1Aj02PWO+h+uoG/HfwfJTbbP3OVJ9of\nYsQ7D0pAmySXaOavfhDit17o5oCzl7duvF9ib7FUnJ36bbdkuQE4VE4OPtbJgR1W/q+3f16ht6GH\nffYecoiYnHfhVDdxwLmL/S1dZfc/M32Rvzr/P0vkjgtSit+/+lPEIlEJC7OAjbIn1yukhnImq8sf\nIS6e5V2/nxsLk/ddEd/t2K5MDMcf2IR7Nop7NorDpMZhUiMTf0yDrOKuwlJqWXC/s5RK3Pri+xSf\naPJndf+fY8eO8Sd/8ic8+uijBIM3J9bZ2Vl27ty57n2+8Y1v8I1vfKPkmNvt5uGHH654TaOqGbnk\ng7KkQ6Myr93tigg333ZF3JybGijR/p9fXuSMO9/47ljbPpxmTbEPz2p0OOoIi/MJp8xKNY9RqQeJ\njKgkr0V45rKXRCpTrGScDydIpDL0DfvJOIVlMcYiw8BhbBphaTe71kK3pZNXrv28OObC4vmto78N\n5B2xr/Z+iT7fVTzhGbpMm+m1bsuzdy78023Lv9yK3r3F2MbXe8orKe+Xhe12bLeKKu4G3Mu2u9YB\nnwnGeODJ+ZIgOOTnwUXZJGCiRiahRi5FVSur2DTcHfahU9SxzbyZy7PDzMRmiSbj+T5nth1c8F5m\np6WLLlMHofgCY3OTfH7TEeaWF/BG/XSbtyIRS4pVLVOxKT5nfQpqF0s293KJrCrbtQ5ux3YnYmOC\nz3MiNgYc+chjKmwKhwPj2JVOapeaVlVINpT4BimtCxbzjI7VOsbZXLbYO6DT2I5NbcYV9uJa9NBl\n6qBN38JLw28QTy0hl8hwRyokKTNprGoTSmdtXlojm8JZZ0cukZHL5Ygm40U72mjlfRV3Brdju+Nz\nk5xZsYvVzO5cLsujrUe57B+uWH09NBHiL753CYAvPtzOuQoVuf5okAatgj22bsbmJum1bqdF24xr\nUoIkIioG2debm1ZLuhT6X0ijTqKqyaJE4erzzS1xfj7x1s3enREvV07033aCez39/So+Oj4On6GS\n5JlZr+TFly9zqNte9p2uZnm98IVnmU4NEYzNYVDpMakMJcHF1QjE5jCoGjjcuIfpBTcHnLvQyJWM\nBMdIZzM81vYg3oifbC4rGLh0aC1cmhlkv6O3yLa0aswsJiIM+IeLyc9oMo5RrScbSwsyPZrqHJDL\nB/3DiSiHm/awtaWtou1WknASiUT88dHfYbOxyvy5Fe6E7b4/9QFQygwrsCCX0wnemTiDUalHr6ov\nk5YHWE4nuB6aoFG0G9dIjE1HJfx44gclbEm5RIZVY8CkOkw6m8YXnWUmGijp81M43661MBsN4osG\n2GKa5+vPdwPwYMBRZOV0mTpYSi9v2Jf8tOfQajFKOW7HdivFbhRRJ4uxZJnPBzkGAv2CdjK16MEf\nC+CJzLDf0QvGCeQyH69PuXhi6yFBFlgovMx576Wy96+V1haPKaQ1HNy0ncHZd3n3xByBhHDh9Wws\nRJepgbnFJDrf53ni8+1sbhS2hbPuSxV9kzZ9E0vphCBbtFDQvLZo8MFdzmIByUYKqdf604f2K/L9\nyafKrwHWTSTdC7gd2x2amoecCKlUTHtjPal0Fk8ghieYY/0mFlXcC5he9HLBe7m8l7xtx6c9tLsW\nn2jy5xvf+AZ/8Ad/gNPp5Ny5c7S3t9Pd3c23vvUtwuEwEomEvr4+/uiP/uiOv3cksyCYGYxkFgAq\nUk790SAjoev0WreXSKUopDUM+K9wrG0faqWcGpmkjHLY6qhngSkueMsZRY+353VQXf4oRw7WFisZ\nm6VWZJFGSCGo5Q83j2trVMhXGtut1lvVyFVsNrbyraO/zVlXHzORALts29nvvJlkOTN9kf/R972S\ncV3yXUUhralY0bCRSodb0buHJkL8Py9OAnp0WiunwglOMYnu31jvW0etiiqq+HSx2gGXSsX88nED\nE2lXUUd69SY6lPLw3IMHWIgk+Pn5aVQKKa1yu2DTcKNKz8npc3xu0xGatY6SCuEGpQ6TyoC2Rs07\nE6dJZlIccOwitLSwIj86j0GpR7bCzDjjvoihroafTb1EOpvJ933JZUhmUjg0Fgb8w4Kfrarvf3uY\nXBCWiq10/MNg7abQFfYgl1xkh+gp/o//7uI//84REqkMrXYtOo0Ciz6GSN7B4nIYZ51NUBtdLVfx\n9uSpoqSXK+zjkm+w2Ax6vQp1b3iGh5uOcsJ1cpXsjB65RIaoMOYVO7qdyvsqPlkU7GNtb0V3eIbf\nO/S/rXvt6rnwh++McfAJp2Bg26DS8bPr7/D+9AfFYOZJ9xnsWgeJkINu8dMk61yI5EsEY8JBmlB8\ngeObH2F+OUw4EcUb8bOkmMJQV4t4XlwW5KzUS6ia4L5/UEnyTCoR88rJCd48O10W+C0wFM5e9eJL\nXOT6/AR77N2cmr7AIKNsN20RtHGL2sDUnIt4epkHmvfxw8HXSuxvKDDKbls3CqlcWGZbrmKnpaus\nN+tQYJTnOh/jemiieN1F7wA7lA/yZJsJV8SNPxrErrXg1Np4dfQXLKfzVazTi17emzrH1/f8CwZn\nRwUDgZXWfG94ppr4+QQxEhzHrrGQzeWK3/NaFqQ77COciJLIJAXv4Y8GaXbM4tzr4XTAz6OtRwnE\n5/CEfVi1ZrRyNelsmtlYSDDWUEgw5tdyERMLLiYWXJxyXSgGodeycr75xp9W/Dx3G6rFKHcGhdjN\nK1feZ2bZhVFuxyRqY3Qoh6ImP8emMlkO7VeQ0kyTky/juoVMZYuuscQmPREvfYGLfOvob/PV3V8u\nvWhFYvWCr4/pyBRWjQVtjYpIIsbDm46Qy0C3bXORpSNf2ZsJzdsmVQPvTJzGrDTRYnXw2sRPeXHI\nJZgwcQkkdgCCsTkCsTkcWqvg3H6oaU8x8Vh4LrPK83znyk9o97RwrHU/p6Yu3NJfWe1PFwq9hApf\nBv3XNsTGux/h8cewm9RkMzmQkP935XgV9z4K8fu1+x1/tJyxV0UeH1vy5+rVq/z5n/85Ho8HqVTK\nm2++ya/+6q/yu7/7u9TW1qJUKvlP/+k/oVAo+P3f/32++tWvIhKJ+M3f/E00Gs0dH48n5l43M9hc\nJ7zBbal3ks6ly5w1uUTGA015qTKpBJ4+sonZuTjRpRTqWhkmvRKZTMRsLCg4+c+uGOi+fXLemH3p\nZiUjXuSSyzzt/BXSlOupAzi1VgAkIglPtB/DG/HjjfjZaenCpjGTWEV1S2czBJfmMaj0JfeoVO1w\n1n2JHebOdaXb4NY9gSotRqsdtZlQvOR41VGroooqPg2sdsC/8ISen3j+V8VNdJepja/s7uS//Xig\nuBHS1SmRLwhrsxeajzp1NkLxhSIbaGBmiDZ9U7F3m1wiw6DS8eZYuSzXo21HUcuVRJJRkpkU4hX5\nznQmH6hXy5TYtRbB9aKq7397sGlMgsxam9Z82/ccmghxasDDnOai4Pqb1rs5sL2bH7x9HYNtidrW\nKXxLLmajOhTSGi4verCojYKbUUOtrqSXS+GeBXbF/PJixc1ye8MmJsPjgsGjR9uOIpfIinZUqfJ+\na4u+7FgVnw5sWrNg8ZBdayl5PTQR4hfnphidXsBiUNHurCMHiMUistkcy4k02ZADuaS8IrdGUkMk\nGWW/o1fAbvrZIXqKS2+Z6OkwYmoexEX5eDoNreywdPIfTvzFzevxIl8ol4QT6iVUwO0GJW8lyVLF\n3YfVUlNXb4Qw1teikEs5czVvX4lUhvcu5RP0hYrsbZv0dG0yUCOT4o27UMmUXA9NFm2uRlojOKfW\nK+oQiySYJUbG56YE5+yl9BISkZjH24/hCfuYiQZp0jowq034YzMVWW/XQxMYVQ3FfhY6qY1XXl8A\nRLTYunhwp40JVxiv83Ix8VPATktXiVTR2kDgreS3q/hkcLR5H6PBG3gifrYaO1DKalkWYNVYNSZS\n2bTg2txYb+ONsbeLa/v0opcHmvaRA/p9gwB0W7aSzqaFfYpsmsONe0hnMyVycauD0GvZC5sszYL2\ns6m+hRdfvszAWOiukVerFqPcOQS9tYh929jl2ExQPMZQ9AS27U6US01IxA20tGd5M/B9kvPrJ1+M\nKj0L8fCHViM41LoNiUjE1LVJ+mduxtzkEhm/1ftv6PPeZBolMykUFeZtu8aCXCLHqDDz5sTLJCOl\n8+Qz9l9hm6WdrS0NgsVUAFatmX7fIN6IvyitHIjN4ayz8Xj7g2wxtvHd9waKssyXcz8tYSSfdp/n\naNN+wec8FBjnT148g1mv5HC3FZc/QjabQ6etEVSRkEtkjM9PVwtfKmBPlwl/KE4ylSUeSSOXipHL\nxOzpMn3aQ6viE0BzvUPwN9xUb/8URvPZwMeW/Nm2bRt///d/X3b80UcfLTv22GOP8dhjj31cQwFu\nnRk0qioEVJQG/HG/4KRbcMa2thg4PzFE0jJNJOVFLrMRjDbSXd/NGzeE2TvuxfzxBckNwXsHuE6H\ndit9kitlY2rTdEK6yQsAACAASURBVALQXN/M3/b/Y1mw5td2fuWWdNNCtcNafX/XopcvdD7Gz1f1\nBSicV5Bu2wiVtRKqjloVVVRxt6EQ0NYoZfhz1yvKAKjlSrbo8n16tndL+O6lvMMvXhCX9F4xrPRY\nK2y2/dEA4UQEg7KhJBA/HBhDtsLeNCkN+CKzgu/ti8yy2dBW7PMmVD160LlbcA3baur4eB7aPY7G\negeXZvLBldXM2qa623MoC1WCOm0N6p3C7KFQ2suyp5mm1jSnYj8lGS7VId9r38m5lT4/kO/7Z1Dp\n0CnquDRzVfCeqxvmVtosP7RpH6+M/KKi7dk1luL6X6ny/miv47aeSxV3Hlq5RvB71shVxddr5XKm\n/REGRgPs6zJzYJuVU5fzPuLokIgHPref0NJcSf/I855+mursSGrFgnaT0rsBEzU1EkSLzrJeKwWf\n8uTU+Yrz7WpmeyqbolnTcscS3B/Fj63i00VBaupPXjzD1fFQWeV/Jgt/+rfnUNXKmA8ncBjVRSnD\nnmNWhsOXSwKXZ919PLP580wtukvW77cnTpPNZUuK/dbumYKxOQLMcXL6fPFvA7NX2cYWdIo6pgSC\n6JCXJjKo9MXebLKwg1RmeaWgZJR3oifoat3CYHC65LqNSLzeSn67io8fZ6Yv8v2rr1YsGi1ALpER\nS8VRSITXZoNSX1LUIZfIiCSjRds1qwwkMylC8XnBcfijIWwaM5ML00jFEpKZm2zKkeA4Y+75Mtm0\nBw+bBccS95l49/2J4nl3g7xatRjlzqDQY3LfXjmvB366ipXuRS7pY6/lOO7UzQT4eskXh8ZKNper\nyDRfr1jjjPuCILN9KHiN8fkbJccLPS9FInAt+oq+yWvX30YqlvB0u1VQuvt6dIiX/3aOb/3aPvY7\nesokF+USGVq5unjs7CoJ3UA0WMLaWY+tE03GBHtv6aU2Lo2HuDgyS41MwuEdVt7r9zIfTtAstZap\nSOgUdfjvcOHLvQSxOK9PkMpkCS4sYdTVIpeJkYirTX/uBzTV24vS+AXIJbJq8mcdfKKyb58mWuob\nKzJ7AC56++m1bi9m9wuLyEXfALraOsF7FgJxviVXXqNzblXlomSAbUtGLGqj4Pua1UYAJsKTgvee\nCE8RGevg8Y5n8WXG8UZ82DRWrJJW3v7nDE/vgAHviOAGYMB7jamwYt3NQWOdHYfWWiZlJxaJadI5\n1pVuq6QnXbj3qfGrnHNfxB2bxqFqZJ9jV7FhbtVRq6KKKu42fG5vIyf7PTRbtXjjFwXPCcTmOaz5\nAiG3AlrhcqivOA+u7r1yqHE3H3gGSjbszfVOMikpirCTR42bCYrGUdXKGJuboK0Q0BStJz8a4MGm\nA2SyGWZjQcHgz3lPP1/sepLx+Sm8YT8OrQWL2sTI7BgHGnfdoSd1/8CzOCPIrPUsztzW/Qqs10ob\nPABrrYO+yDI2rU9wM5nIJJCKJZx197Hb1o2+VlfsV7HV2CGoTW5RG7m8Igl43tPPfkcv2bQYd9SN\nQ+3ApNbz05G31rW939z7L9nUkO+P+GGaPFfx6SCajOVtN+rHG/Zj05qxqc3MRm/Kr1WSy4kvpzHW\nK9AoZUTiKUKLyyxGEwyGRktY8wDNOgfXQ5OCYwgmPThMm2ixannpRIAdO54ipXcTTHowyO00ZDbl\ne0xe/J7w9bF5vth5nJG5UfzRAM2aFizyZhTSUibE7Qa1b+XHVnH3w6xXcnU8hKVBWeyXWlsjRVMr\no6NRR2B+iW2tDZj0tShqJDSaNSiXFcDlksBlNpfllWu/4OGWgyuSQaWJk0Kx30HnbuKppZI9kwgR\nF32Xi+cVigsTmQSnXB9UlJQzqvSMBSd4pv1xbozBtWF44GBtfi+5UkE+Gw/Qtaa6fj35zkIg8Fby\n21V8/KikrhFZExAufJ9rGQZGlZ6GWh1TC6XJw7Xf//zyIs46OwalvszOxCIxu+3b8YZnBCWMjTI7\nPzlxg92dZs5c9ZHN5uWS3ju9xFe+8CtEZBNF+9GkWvjHH8+W3P9ukFerFqPcGZxZKfYQN3hJzqTK\nktxa6wKTs6VFS4XkSzqbZiYaoKneTi5HMflSiRm0XrGGKzotePza3DUaNU0lbPxsLkuf7wq77d2k\nMqmibyIWiem1bscd8QjafTDpQVXr5ESfm68/n98bnXH1FaUU62u0LC6X9vEuzO07LVuLx7pa9CSS\n6XV6vs5gUhlKnkEh0Z9ILQH531CNXMozR1q4PBaiXbON4XBpMiqWirPV2C3I5q6yOSGdznFu0F9S\nyFQjk/DUYeWnPLIqPglcD04K7neuByc/7aHdtdhQ8mdkZIQ/+qM/Ih6P88Ybb/BXf/VXHD58mO7u\n7o97fHcMhYrrtZnBBmXeabEpnZx1ny2ThTtgPYBMIpw9NtfkE0eT8WFBJ284fAV7nYXL/uGy9y3I\nb5jkdlwCQSCz3E6jtY5//OEMGqWdZmsnfb4wkXiEJw42A5UXSVd0iuWccDKlsDnotnSW9fyRS2R8\ntfdLAGSjOrLuLlSBZrLLKrINuhVN1pv3WOscjATHOTsxyHcv/fXN+65ovMLXONS6reqoVVFFFR87\nVstYrCdPsVr25/CTzdgkRsZiTtyRm3NyYZ5r1W4ieEPORd80GcUi1+cmy+6Xl3OZRCVTFpM/+XVG\nx7uvKcmRYj4cRS4z8sWH23m+uYOFnJehwCizsSA91q4K0h8OXht7i46GVkwqg2DwZ7dtBz8a+hmQ\nDxD0+fJMkErSA1WsD5W8lp9df7tsjbzd51lgvaYyWRprOhmWlFcbqpaaUNVW3kwGYnPFzaRKqmIx\nkSzeo1IV5k7zdhpq6xkKjKOX2mhIbcZ1Q8quTVt4K/RDor585Xkl22traCkmfgr4tJs8V7E+nHU2\nXh55E8jPBf2+QfoZ5NktN5n3lVjYs/NLZHOws8OISiEjtLhEl0nHQOhSCWteLpFBDsGgI0BzXRNJ\nk5q3L7jZ3KgjG5XQfzFFvdqJK5zg4T35psiVJKocagc/Gf1ZcR4tyMk9bn8WT3yKQMrzkYLaH6W3\nZRV3B7a1GvDPxYtJHoVcikYp55WTN4p7DHcgisYQZdfDs7iiF8gonTxf90VGQmM80LSfSDKGNzyD\nQ9WIsdbMe67TZfs5yPdSPTF1tmw9OL7lUc64SwtG5BIZ2VyOhlodiBCcl2skNdTVannl+us8UP8s\ntTUZcrpJkv7SpNNaSbr55cWyhFABqwOB68lvV/Hxo1IvEW/YXxIQXv19rmYYDM6O0mXqQCouDdOs\nlm8tnKuQysnmZGV2tt/Ry2ujbwlKGPf5riAJO3i3z02NTFJke9bIJOi0NZw9l+C//O7Nviy/9X+/\nU0wOrcbtqnZs1Ee/FarFKHcGntkYv/r4Fs4t/5BH244Sii8wE50tJk6uhUYxr0lkFIre9ti7+fym\nBxidG+e06wIAyUy2ok+6XrGGQ9VYsv8qwKK0Y8y1IZeU9tExqQxML3hKfBMhZYTV0t0GuR1XOFG0\n3QONu3h99B20NWrGQhPIxDJa9c23HPvRXgcn+z1sUdnxCIzZoXaSCzlo0E8TSnkw1zgQLdg5dXa5\n5LzrrgW+/c2Hiq93BAxliXuAU64LH+pZ3i/wz8UFC5lm5+IVrqjiXoJWoeZn198GSvc71dhHZWwo\n+fPv//2/5z/+x//In/3ZnwHwxBNP8G//7b/le98Trti7G3HRJ8zs6fMN8OXupzHShlxysaRySy6R\nYaCVOoUcueR82aTbps7Lr/mTwhIurtgkjvo97LZ1k8qmKPR1kIlliDL5R7/F0M6V+bw00Gppmc2G\nNjrqjPzw7TGSqSyBhSWSqWxJoqTSIulUN1GvVoBAgXJhc1BJv/rG3BQW8eYSGvjFEUqaqHYa2rBp\nzKSzGVLZFM46O1KxhIbaes64hBvcnff0cah1W9VRq6KKKj5WrJUzqiRPIST7I5ec54WOF+gP9pHO\nZoqNzIPxOZYzCVDOE1hIMRqdrhj0dGitiEQiLBoTcokMqUhKLBmn7cA8viU3zVIrskgjV8aCjEzN\n88vPWHmgaR9zSwsV5Zo69C184OnnvKefg85dJDOpsmqy1Wyg1RuhaKrqAN8Owiv9ldYWOYST0du6\nX3dbA4lkmg5nPa++OcvuXTeZEEa5nSbFZsaviZkPhyoygyxqIyCisc5OfU090rAWuWRgZY3tL1YO\nLy5F2KRvpK5Gw3BwlH2WfTxse4KfvDfOT/q9qJVS9JsjJVIYYsTCknAtB27r81bx6WFq0VO03QKS\nmVSJBFUlFrbNoMIbjDF4Iz9v/OunOhkOvs8T7ceYXvQSiIWwac1o5CqWUst0mdoZCoyW2U19qoVX\nr86QSGWKlZi7O83FAGPBj60kUbVW7qjwGSajk1iX9/AHT//rj/SMNtVX7mtRxd2PoYkQf/G9SyXV\nvhqljD1bLSWBoEP7FXk2je9mQVp/sI+nrL9Cwq+mXiHFNTxDtE7BBefJsnVdLpFhUhmIpZcE9zau\nRW9x3hSLxCU+g11jxqwycnzzo4zNT5TsPftnBtlp6SKajONJXyeVbsYTd5V9zvOefo61HGRheZGZ\naBCjSs+Whg4GBX5z1UDg3YNKvURsWjM1EjlGlZ5AbA6b1kxznaP4fRZiEHKJjFppbVF2sPBdp7MZ\nNukaUcpqiyy0aDLOJl0jT7Y/jCvsZSYaoLneQSabEbTZLFkeaj7E+V/k5ZISqQzJVJoHDytZVk0R\nTPtwqBoZCdiLCcQ7qdqxUR99o6gWo3x0HN1lx7/swaQxMDg7ikVtosvUwYnJs2RzWR5tO8rc0oKg\njygVSfjZ9beKEtYFrGYGBWKhisUahV6YnkCMXbu20he4WPYeB5y7+PlbYfZajpPS3cATzsu8qWRK\nYit9VQvnVpLFLEh3F5g3BdsdCYyhU9bjWvTSWOcosoR223YgEonwhmcqjn1PpxmTNoM8UP5cLJoG\nfvTaMmDCrG8mbVBxdrA8MLf2N1QpcV9lcwpjeibP0iokrgss4KmZyC2urOJeQDQZF9zvRJKxT3FU\ndzc2lPyRSqVs2bKl+LqlpQWp9LOlGOfU2jjluoBarqSpzs710ATRZJxDjXln+fwHSXa0lMpSyMIO\nzp9Psquzjh2i8r9NjElgb76JrlBjaIfWQk3CgFmdwBueIRSfz28G1AbksTyNZjoyJSgtMx2Z4nj3\nEX7nSz2cvuxleibCnq1mDu6wFZ2cfY5dgovkXnsvDVoFb914v3LfnnWqHhXBWcEseoHevam+hYHZ\nq6SzCULxeQxKPXKJjE26FgZmXhe8rys6Vfz/R3HUqg16q6iiivXmgUpyRmvlKSrJ/txYmOBx85cQ\na0K8NnazD0qh8vyBw88ynnDhVFjKNkIKaQ1OrZXx+UlC8XmMSj32egtvjL1blCry4EUuucwh+3P4\n52q4HhvkvP8cDo0VESJe6HqasblJPOEZ7FoLGrmS4cB1jm9+hJdG3uT96Q840rhXUDpECAV50jv5\njO8HzERm2e/oLZNG9UX8H/peQxMh4stpVAoZ6UyOpUSak6fT1MhM6LR5JkSyVYy6Vg6ALNKIXIAZ\nJBVLi9XBR5v243cZeLzrWfzZcTzhGaRiCXZtE5MiFyPBcQxKPUpZLROLE/z4Z3MY6xUcf1zHLGNM\nRDwcdO4mnU1z2nWx2Esok8swGw0WN5fZqI7vvjfwkSt0q/jksBHbXcvCFotFPHCwlpxuGLnFRY/U\nRrOmBb/4Mr7oNGKpBbW8lkyunkw2SzQZ57ynn4u+Kxzf/Ahj85MEYnM0aZ0k/XYuXEij09YwE8on\ncBKpDOlMlmeOtHB4p53O5rwNrZWo2lTfAvM2+mdPCX62YMrDCzuf+8jPyJBrEyzqashVZVQ+CxBa\n51W1MsZcC8XX6/VjcKdG8F5voadXiqN3Ek/chUNpxqoxMRQYLSv+SKaT7Hf0FqWDCvCskvYRrDif\nyTPutujbaagNMj43RX2tlp2WrmJPwGDSAzRhlttX/IPSgoPQ0jzXQxOoZEquhyaQBjezQ/QUab2b\nuYyXzjWBwPt97b4bUKmXiFVt4pVrv+Cgcxd1ei1TC27EORHHtzyKa9Fb9PtUslqSmRTL6WUeaNpH\nOBnFF56l17YNfyzABe9AiZ0NBUZ5qOUAM5EAiGByQbgoFfLso1qNntDiTQaC0b7MqdirJU3r+wIX\niz3QhFQ7amuk7Ngp4W8u/NOHsrWN+uh3K+7F31dMMsvJyI9IL96c9wZnR+m2dCJCTDA2j1wi4+GW\nwwSX5vBFZjGq9NRKa8nlciWMtAIKzKBD1oP8+vYv0WrPs31XP7/W+hbqclZmlRMs2r1cmbPz5a7n\nuTY3ijvsw6G1st2wnYH+NP65JUQiFV3Gbjz4GA6MsdPShUNrLSZP19sLBWLz7K99ltfemi8WoKwt\nAiywhHbbdtDnu8IfH/0dNhvzPsHQRKjEF9ZpaxiZnsetG6hYXP7ovmf46elJpv0RWmx1NJo1JUyV\njSjfrGbJdbd18bVdj9Hu1H3k7/xegdWowmnWsJxMl7CAM9nsrS+u4jMPX8R/x/bq9ws2nPxxuVyI\nRPkqkRMnTpDLldN/72aYVIYSveY2fQtKWS2mFdk3k17JydMzJcGYRGqJfV11ePwxzg4uoVFaaLZ2\nMOgLE4kv0WTNZ5U1cpVgNYRarkKrlfP9K2to1zMy/vXWrwKgqBFXlJa57prnL753CblMTLNVy8D1\nAB8M+WmoU7C1pYGloIYeydMs17mKSSlF1MlSUMOW1qZ1qwQqSW1sMbRy4f3ZsuNwk949E50tczzl\nEhlmlSnfkLcCG+mjotqgt4oqqrjVPFBJzmitPEWlBLg7PsXkkBNLd0AwORSWTWIROTjvuVCi0e7Q\nWmnVN/GDwZ+WzI2DgVF6rds56+4ruU+sdgqZtBnvSrXvQmIRs9rAP1z+MS90PY077CsJJPXNXOUL\nnY8xGQzQptxOSuZgaWXutygakcoygpWmndVm6LeFXtt2QcmUJzse/lD3WV3lamlQ4p69yRxKpDLF\n4PhCJEEqk+XAdivZeJYjpudZUk7hik4WG5AXgoWFqqbtO6T8aPplADoN7RiUDbx6bW3CUsbj7Q+h\nrZXRuCnNa74fsNPSRZ1Cy9jcJEalnmc2f55Xrv2Cs+4+jtgPU+frIbtcS0Bay7f/v7MsJdLA3dPk\nuYr1sRHbLbCw373owj+/RFtHljcD3y/KTnnwMhweYLetm27zVt4cPyFQaJSXURmbnywGpzOkkYjF\nNNQruDoeKhlXYH6JX3q6gfenfs7/GCkNnK2eV0amQixNTuMKl/uoHfpNdyTw8f7pZXY0lxd1nTq9\nzAtVsttdD6F1fj6coLvDiH8ujk5bg1wqqSih6Ym7aN3cyJuBHxXt2hPxopDW8ET7MTK5DG+OnSj7\nDRVsvgCDSodKpsSqMZHOpgV9hslFN2OhCVp1zcRTS3giMyXnGeR2Ls0t0Rpt5KAzV9JXSCmrxaDU\nEYjN0aprxpjr4NTpZbY063ioYxdbmkrn4Y2u3fdiAPtuwoHGXUQTSwzMDq70YLRi1Zh49do/s9e+\ns6RB9cSCi76Zq+yz72SbaTPRVJRroRvF4o3B2VEiyShdxs2E4vPEU8IstGgigbmmiZnl6XV9QqNK\nTyKoI5HKV0bXyCTEa6dIhiv3QBNS7dixU1Ii875RP3GjPvrdiHvVN/am8smT/Y5eQcm05zofY3Le\nxfj8FEalno6GFk67LrKcTtBj7QIqSw/LYw7+yz9e4je/2I1YPV/y/GwaM6d8L9+cg/EytJAvREpl\nUvT5rtDnu8IO0VO4A8s0taYZibjZYmhDJVfy+vW3i4n6RCbBwlIYk7pBWD5b1cRIX5bH9jcVi5i+\nc/YNwd8SwB75cTLRejAKs9VqZBL2b7OSkFg4675Y1jZip34PgxNz/IvHNuOfXyYaT4II9mw1o1bK\nkYjhgZ71i6mE3ne1Ek8V0Nmk559+fq2s58+XH9n8KY+sik8Cd2qvfj9hQ8mfP/zDP+Q3fuM3mJiY\nYNeuXdjtdv78z//84x7bHUU0GRNMWBQ0AZssGgZGSxse18gkNFk1JJJpjhysJaWZJpi+SFdbXrZH\nK8pTNQvN5dZm/eUSGX1+4aaPl4MDPEx3UVpm7d8jyRgfDHl57rgSX2YMb2SG3h0WrJI2Tvbnq2M+\nGPFz+nJ8TcIqTmqHn8/ta1pX87mS1Mahpj0kp2KMuRbKKJQFaqor4haWPwi7+VzT5zjvL6+m3Gvv\n3fB3VQnVBr1VVFHFreaBjcpTVJL9aa1vYe/jnfzjxEnB9w8kPXRKHkQqvlRkYTzUcpAPPP3ryg2s\n3RR54y5S6UZalE4cdRaW0wl0tXXoa+uYXHSVbV6SmRTTi17mhzZzWZ3l/YGbc/8H4QR798iRS/rL\n5t4tuu0VnmRlVOfafJGD0DOYiQYqXCGM1VWu8+EE21obmPbflCMQi0Uc2GYlm8vimY1RIxXT0yPF\nn/OSWlqiQakvbiZXwxOeob7BVTweTkRwh72CY/aEZ7BtE+NLz7PT0lW2uR8MjLLf0csF7wBLfiPn\nrubZYm+enS5KdRXwWarQvV/xYWxXJBIRjiWZzU0IXpPKpgjE59ad1wKxOVQyJf5YEJlERpuhnmxU\nV1bdfeigomLgLBvVlfSA2LdTmNn+UOs+4KMHrzubdfzs9GRZwdcTB80bvkcVnx6E1vlUJsu2bSLE\nTj/BlBeL3IFUJtyPoUndTDI3TTJSatfL6QTzS4sspZdvuZYXeve8P/0BDq214li9YT9WtQmJWFJk\n8xSwugF4JpulT2Cfut/RQ5epA4lIzAu9+3nhQMH+f87fDJfa/0bW7ns1gH234Yp3nKG5UZrq7AwF\nRgHosXZVTBKmshlOTp9b0+dMViweUsoVLC5FCMSFkyRTi9N0SR5mbMC2rk/YJNvK90/dLEIx65V4\nl4SZQquLpNaqdvzNhX+6LT/xTkrIfdK4V31jf8K9rmTaaOhG0Q9da5fB2Bydhg5Iy/mljucYC4/h\njfiwaaxYJa3cGFLgn8tLu4kcg8X7r/d+sVS8ZK5M6908dqyFU7GXSIZSyBdkdJk6in9f3S/LojYJ\nJqEc+gYe+4q95Hsan78h+DzcizMkRlqRp/K+biW2WnQpiSbWVGTqr24b4dA3ENhykilpI2K5ndPn\n4mSzOaZn8smJjSRwPkmW3J3qw/VJ44Z3UfAZ3fAufkojquKTxGwsKDiHzK6Sv6+iFBtK/mzevJlX\nX32Vubk55HI5arX64x7XHUflJEveARKL4bkndXjTo/iW3HTUOrBJOyAGW7eJ+c6ln96kQ6/I9nx9\n59cAONS0mz898V/zTtWKpFwyk+LfPfS/853zfy84HncsL4PmrSDJ4wnPsL05zv8cfHnNRuAqx5ue\nz7/258e+unoYwLVyfL3NcTaqE2QNZaM6jvbqiMaTxJZvUihVCmmRmlop+OWPBuhtbOfrqa9x3tOH\nKzqFU93EXnsvh1q3VfxuNopqg94qqqjiVvOAkDyFELW+kuyPTdbBf/5fF+k6YsUt0HfFILfzi3fC\n7N/zNBKzD1/Mw8JSBJlYto7cwBw6RV1JLx670snFyDKf17Xyw+s/AKChVsfnNz3AqZWmqWvhDvv4\nvedf4P/8n/kG06vn/lNnl3ns2HNEFVN4465iJfuVgQyHBMg/660P1bk2v/kTPl5eUbgeVle5JlIZ\nFHIpNTJJ0T4PbLNyYdhffN3Umub7Ez8tBhe3GjvKfBcAm8ZCTpLvM5HNZUll0xXX5plogFRtmnAi\nQn2ttmKlY6/0GU6cuulLJFIZlpPpkvHCZ6NC937GRmy3jJEm0G8E8rYxFxdmgxfmNaMqn6CEfFX5\ndGyc2Iyh5FyNUkZQNC5oe++Mn+Pkazoi8fzfpnxh3rko5Xe++jVG5q+UsdfvRPB69TpRmEM3IsFS\nxd0BoXX+gYO1/Gj6H0qqyA86dwsGApXxZoaz7wreeyERZi6+IPi3YGyOTmM7SlktNo2Z10bfwqwy\nsLC8SJu+pWKfl6HZUeKpZY61HGJpOc1kZIomdROZkJX3Ti9RI5OQ1AhL1CUzac57zmJW5X9T69n/\nRtbuezWAfbfBHZsmmowzGLgO5APUT7Y/zGX/sOD5nrAPlUxZTP4UgtmZXAa1XIlJ0kyDLkKOXEVG\nTzA1xny4gUQqU/QJF+WTBJIethpvSrku7r/J4Hlwl4NTQb8g03LLOszx2/UTN+qj3424V33jJm0T\nqWxyw3uY1Ylwu8rJ+NlGPv+Qlh+O5mNeOkUd/TNX6OcKj7b9MueHMngDMSKKm89pfYm20vdbzM4g\n16aK7DShawvJl0u+q/zyiny2K+zDpjVjU5v58fAbvDzyZomfYJTbcQns88w1DqbJFX3dSmy1wPwS\nvqCI/d3PEquZYmbZjUNjRyLN8bPxn+eLuiJ5Kc9D+5/i5Mpcr9PWcGrAc8vkyifFkrvTfbg+SUx6\nyxPJAJMCCeYq7j1MLZSvW+sdr2KDyZ8TJ06wsLDA8ePH+f3f/32uXLnCN7/5TR555JGPe3x3DN6w\nsPafZ+V4lFne9//4ZqIl4kUuucSD2l9iaN4j6CiPzF/hENvYYmzjN/f+Sy54LxNOROmxbmO3bQet\nDc3YNML9gOxaCwA2jRVXhabhwwtXBN/XlRwFjuIwq0sqiIvXmtW33Byf6HPz7un4Gim7OMqsm6O9\nDs4N+ssolE8e3gSAs84q3Oi8zgbAodZtdyTZsxbrSdVVUUUV9wduNQ8IyVMIVTAJyf4ook6uXs4S\niacq9l3Rp1vYu1XDVnMDwUUrz/Uc579e+q+CmtcFrA6OFu5jErfzzJEGpsIXeKjlIKH4AjPRWW7M\nT1dsFmzXWPnhW+O0OupIpjNFViZANptjwa/i2rQFmdSOK5wAkmxvjZfd51brQ3WuzQfs1lu7N4qu\nFj0zwRhmfS0gou/aLLs7zeRyOfxzcRBRov9d6FFRCPyo5UrB4KVIBO9MnCrKEM3GgvRYu4TXZq2V\nq7Mj7LZ1PAHe5gAAIABJREFUMzY3KTjO6QUvkaFGstlSSd/A/FJJ7xb4bFTo3s/YiO2uZaQ1S60E\nJIGSXiOwkhDXmAX9VKNKz/XQBDWSmhImhEasxGDR0lCnIDC/hFFXy+5OE+8u/JPgeMfmJ1DVmorJ\nH4ClRJrL/Rm+/vyXy86/E8Hrja4TVdydWPv99Ww2kDRdJjlZahdn3X082foI/sg8ntjNoohfvBdm\n50M2wR47eZuvtHezopYrmZifxqwy0G3Ziic8Q7umhaZ6B0OB0fKCErWZ8+68ZGdsKc0TzU/y+qkp\nfOMxdFoFPR1qcjkIpS4JflZ32Eddjaa4/q5n/12mjluu3fdqAPtug13lLJFBl0tkKKQ1mNUGQdtq\nrLdTX6Plnckz7DB3FnsY5HI5nm9/nqmRWpK269RUkNeqldbijXnpaGxldHqBRCpD0FeLa8bO1pZu\nHtzRQqtRB0bK5jmRqrIaSCXcrp/4WZ5771Xf2JBtZSA1QJumcgJbLpYRiM8Ve54FYnOYVAaYd+Cf\nW2I0Ml20n9WFbtPJa9TITNiMKqSmDhLpBPPLi8wvL7LDvJVUJlXGiDSq9ASic0U7b9Y5uB6aLP59\nvf2WTWPm/ekPMCj17LZt5+2J0/T7Btlt28FZd1+Jn7BJuZWrAuw4s7iND+YWeXiPE6jMVtvcpKO2\nRsLw6Dx24w6SnibSu6Y55ztXcl4ykyKld3O0p5voUpLA/BIzc0sMTYTWtftPiiX3We7DVTEWavrs\nERWq+PCwa80V971VCGNDyZ/vfOc7fPe73+XEiRNks1leeuklfv3Xf/0zlfxxaOyCzpZDk5/Y48op\nkovlzrS4PsjQLRzlkcAY59z9xFNLhOLziBBxzt2PrraOpnobl2aulC0sjSuJkh3G7YJ/77X08JPR\n1wTft2DkW1sauDicr8gsyLMBbG818P7UuXU3x8OT84JSduPufLVbIpUpk30rLAKNWjsXJQKfSWsT\nHO+dwnpSdVVUUcX9gY3MA2vlKYQgJPuj04JcmtdBP3V2mUP7byaHLAoHm7XbyETqyMhjnB+coaMT\nXp98rbiZ36RzCgZ/tpk2I5PI8Ib9WNRGNNEtRAMqUPrISpYYnPVhUOpxaK2c9/Sz39EruLm3SFrx\n1ASRNHhR17tolubn7VNnl1EppGxu0nFxZJZUJsmBbVaWk2lm55f47o8GSjbXtwqern3GcokMk8rA\n4aa9t/mtffbQ0dDCJd/Vsu+gvaH5Q91ne5sBRY0U92yUmWCMns1GJBIRYpEYpUKKa+bmpkWnrWEu\n7StpXhlNxnmy42F8kVncYV9RVrZ/ZhCdog4AtTxfLSxGXGI3he9NJpYQTy3TUKtjURkWdJSd6iZO\nhRMl675cJmbvVhPv9N2UhPmsVOjez9iI7a6uKE1lsjRrNiGuWSawqmFq/8zgSk9LOWq5EpVMWRIg\nb6pz0N7QwkXPZXqsXUW73Cl9ktNXfZj1SiDH6PQ8X3qkg5mAcODMLLczteK/rkal6tZbBa83Kl+y\nkXWiirsXhe9vaCLEDc8Cb4fKJXyyuSyX/JfR+x4h6rfjX0qhqhWRy+aoT2/ioJOyHju5XA6lTDjp\nLhaJ+ecb77Pf0VvWr3U4OMYXu55iKHCdYGwOR50Fp9bGj4ffAEBbo2Z/0w5OB9/CVX8Np70ZZbyZ\n985EMdQpaNduZjZe3mvQpjWjkNQUfZz17P/X9/wqb914f13/6F4NYN9t2Gns4VKgLx9LEIl5oGkf\n7rAXfW19iW2JRWL2O3pJZ9MM+IfZadkKiLjsHyaby7KwvEgqm6bZvJuLix68EX9Jv0mjSo+hVk82\nl8WkacDT/A49bVZql5pwGHMoWjy4ls/xyngjj8sPCSbItxjb+NbR3+adiTOMhSaxay10GtsQIar4\n+T7KnvyzOvfeq3GIs+eTbGl5FIt6iSFJ+R5GjJjznv6SnmcOrRWzyogn5OUrz23j7PwVzCpDWSIn\nmPRgNbSwdbuYobkUFo2JxjoHdq0ZX9SPbIXhrpDm+1pKxRIcGiuB2Bw7zFsxKvUsp5cxKPVF3zWZ\nSZX1GCr4u1KxlIkFFxMLLgb8Mh5tPboiXZtELpGVzJ/bLO24ZspVcPwuBbBY9HUrsdU+t7exaMdD\nEyH+6gcDzCSEWdShlIeEt7mYqJj2RxgYDazLrtnWahB8322tBsHzbxef5T5cWqW8TJ2gRiZBq5R/\niqOq4pPCVuNmLvkGy+asTmP7pziquxsbSv4oFAr0ej0nTpzg+PHjqFQqxGLxxz22O4otxlYuzgj0\nQzC2AOCJTRePra4AG50fpVXXIugob6rPXzswc02wn5BNY8EfnRXsB+Rakd9YnIPdtm6W0kvFv9dK\na1mYy1Ss/nauJI7eu+DmX71gYSR8FW/cxWalky3abQxcCjBvX39zfPigglc8Py6Tsvulg/+Ct99b\nnRjyFQOMI5PzAHSZO3CFfWVj7jJ3bOi7uF2t9oJzemrVtYeqTUqrqOK+wp2aB4Rkf2JLKbZ15Xuy\nZLO5FYq+iYa6RqwHFIzHB/EkXNhsZqwtaqbi88hFcuRiGUca9+KN+HmgaR/hZBRf2I9hZW6ciy/i\nDftJZVJIxVJqUgZkhjBvBl4qyhisbSh9fMsjeCN+POGZ/CZL3IpvJsvl3E8hmJc9GA5fRiy6yr/6\nledxxSd5f/EiPcesNNZ08uqbsywl0kB+k3Gy38O/+9oB2p26WwZPC8/49NQFMrks0VQcT9jHyanz\n5MjdF3PuWGhKcO0eC02VnLdeoPlkv4ezV7yCTNoD260sRhNYDepig/LYUoojpu38fKK0eeVQYJRj\nLYeYmJ9mODDGTksXWwxtBONzpLNpnmg/xlw8TCiS4Eudz3N94TpquZLFRARvxE88vcwXOh/nA+8A\nu607GBRIUO6z96I5tkBIfJ1g2ssTzj3cmJ9kIHKB7cesNNZ0MOeu58jOz0aF7v2M8dA0T7Qfwxv1\n4w37i7In46Hp4jmFitIamYQHH1DyumetxLCML3Z8geVMHGWtjB5rFxPzbnaYO7FqTKhkSsbnpvFF\n/Tjr7NTJ1WSTcv5l+6+hqzEjWfIwOr1Ao0XLs0dNvHvRTU5pFQyomyXtJFKhss/R7qznxZcvMzAW\nKvltrRe8Hp787MqXVCGM9ebYoYkQr71/g0ujgcpSrTI7YqmI9s05UhpvcV+jr2vlNVf53m2XdTvh\nWIqvdH6ZgVAfs7EQVrUJmzbP4FHLlYK9KpbTCSYX3HToWzCp9IRi83jCfh5qPohGrmE2FuAHQ69g\nUOrZZdvO1IIHN+/y5Be68S76GI946DJ2ULMSBM3mssglMtQyJec9/Xyu9TCwfvKmtaH5lv7R3R7A\n/qj9vO4WPLy1GxFf5Zz3Ig11Ct6fPs9OSxeB2BwPNh9gMRHBE56hx9rFm2Mnyuxwn6MHs8qAN+LH\nG/Gj0FzmaPN+vn/1Vc66+1DLlUWp+cZNdl6//k6J5KFcchkx3Xwwm5cRdoW9XJy9uK485kXvZXbb\ndjC/tMgvxk9iVOp5sOUABxp3lZ17P+7J79XPbDeqOXnayzGpmmMth5hfXsQTnin6vYX5qCD1BmBR\nm7jgHcCqNiOrm8eWMTG16ClJ5GRzWZo1zWx+WE/f7AdEkjFC8Xl6LF1lyXO5RMYzHY8wGw/y1sQp\njjTtJRRf4MrsCHbt/8/eewfHeeZ3np/O6IAGGrETMgiQCASTGEVSFDVDBUojzUiT11O+PfvW5Sm7\ndst3W7fl8+3d2GVX7W7duuw97+7M1q3t8mosS5rRjMIojAIp5oBAgCCR0TkD6IjO90ezm2j02yCk\noShS6u9f5Nvv+/bTL5739/yeX/h+m2mvNXPDN8NqKlcoki+UE2elKOUygokQ9qCbcCLKfvMuLtpz\nMT9byMm0f5795l3oqmqKkty5dWQXZ0abSXq3oVTJUSikSDQU+Qyb6Vbr66jnh98c4q1Fq6DOnFHV\nwvlAMRPDnbprJuZ87NnWzGoiVeiirpJLmZjzcXiH6dP/wdfhQdbhisaTgs8olkh93kOr4B5gJRZk\nj3GIZCZZKEyTiWUEYxXav3LYVPInHo/zk5/8hFOnTvGv//W/ZmFhgVCotMXufsZ0YFYwkDMdmOMJ\njmJStWLS6gvVtvnFS5RS0KbYilxyocRRblX0ArC4bCnZBCTSSRaWLYCIy47RQlIpL5jXcqtLZi46\nyWXf5ZLPEw1iHmob5IqjlHZoqCkn4L1zj5Sfzv1dEVXdiO8qT/Z8m2blxpVd5bjXnZkpDh3o5JeO\n0sTQyf05+o28k3PeehVRVoRe08j+ll2bcn5+U672rY3dD7yTVUEFFfxm+CR2oFwgoZwzD3B6xFEI\nHsaTaXq2ZnnH99KajYqjIHh61XmNp7Yc543pX5dUoHXWtjG7tIhlxY5e04hcIqde0civR+wMPeIW\ntMHxdBypWMJl+yhSsZQahYZsQskb768ycNTFLuVg0TrVXmvmZzOvFDZENhxMSsbYs/skp8+mEItF\nHNpfRbLawn8e/2sGvL106VrvWPmbf77F9trxpRGGtgYdhQ3p2rV5bSv5RjzZYjGMTXtJJDNFFWli\nsYg925qJJ1OIRWL6B0SIbgmUd8vNLK0iOC+WV1fYUt9BOpPhinOsaNM85p5kj3EIebCVt66k2T7U\nzUehVwsVx2atgdnAAulMmtmlRZ7qOY5txYEz7MWsNbCzeTtjvmGm0vM0KOp42LSHf5p4veg7hiXX\n+P29P6CvtRJAv9+hklfx5vT7wC3ufecEI0xwpG1f4Zyju8xExR5S1TaiitUS4ftUJk0ks4Ir6sbm\nchV1JkrdEvYYh7jkyFFZ2YJOqqQKnun9CiPL53CE3BjNeg62dfPyz11cuu5mz7Zmzp0Lcmj/SVJ1\nNgIpB3VSI9KgGa9NIVi5GU+kePdiLmHl8kUYn/Xzw28ObRi8/uDUg0tfUkEpytnY5493c2HCTUuj\nhshqakOqVkW4BX1nkrfct7VbvRIv4qpVQVu7mo7T02jmXcu76DVNHO94mEQ6znRgAYlYsiF9pm3F\ngVKqwBddwhcN0KCqo0lTz5vT791eo28l9HcZBjFW63lj+r0S3+LRjoOEE1EaVXWMuq/TXdfBhPum\nYGdu/nfmkzd38o/u5wD23dDzuh+QT1iOz/npMg0RVUywQ9/PVWeONaNZ3YBKpoRsbj4IzUOxSMR7\nc6cLGkC2oJNh1wRP9z6GM+Qp+IE99R2IEJHKpEvuEUvFihLuG9Fjfrx4ib7GHj62XCpa+yd9MwBM\neKaY9M5iUrWgjLUhiuo4stPMP9+Tiw3c9M5yevEiP7ny04Kvnb/vDd8s2xq66WvawoRn6oFO7H0R\n4xDVKhnVKhlR1QJzzgVUMiXJdLLg9+bhjQQ41nGAdCaDZdnOHuN2nGE378+fLfYRxBL2mXYgEolJ\npZJYUuNcsA8XgrO2kPCcd4W9iMUiBpt7mfBMldzzyS2PsrhiwxtZokFqIuE0I5GKuJj8ZUkiKV9I\n540EUMtUBBNhkplkSZL7k3ShSSUi6muqkEqEO+K2tdcTSO/mqvdKiX1ukffyUbJUP3Gj7prxuUCh\nSEenVTA+6yeeTNNu0G5qvJvFg6zD1Wms5cV3bgIUnhHAd77a+3kOq4J7BE/UTyabIZVO4Y8u0aiq\nQyKS4I6WFpRVkMOmkj8/+tGPeOmll/iLv/gLFAoFH3/8MX/0R3/0WY/trmJx2Y416CibhNmmb+cf\nrr0C5DbL1705fYbvD34Dn2tVsDsnT7NWTmTZHfaxW7+Dy4wWhOjyMKtbc+ckcnQq6z93J+y45vbz\nhOlZnOlZHCEnxmoDBkkX09eqeLQblqXzgotnQDrHV9oObLg5mFueFxyzdcVKUp0WvK87Ow0cACAT\n1pG0bGXV20KyUU1Gl+MRvhMqQqMVVFDBZ438xhv1EmfCr5YNJJRz+v/Vd3fy/mUbTl+E1uZqtAYL\n2IrPWSt4ag+7iuxaIp0sUHTlaeDyG5InTM8ik6axRSwIIS902nBLJyiRTmKujrClpYuGmmVOLZ4v\n6QrZZRgsUDHkvz9ZZ0Mha2LvQ3LGsreDXtZgeRHsrbpB/uaVUSbmAwx115PUC+vOfRnstalamEe4\nnG5KHsl0hrEZL1ZXiAVnCH2DmkPbjZwbd5LJZDkwYODyZK4T6PA6gfKUOoEsKRMcjy3oAmCnoV/w\nbxJLxRBrHXQYB4gqx0ks587Za9pRCDjl7pObM3uMQyTTSTxhH78Mvl34rcurK8ilMsHvOG8bFqwA\nruD+QigRKQRZ8kikk4QTkcL/xZolhtO/RLdaIzjn9pp28ObMr8sGVNYHFXfo+/n5jbcL/7cGncgl\n4zz/7LP89OWcSLlcJil0U3517x5OjdoZ6NSxmkxxbLeZYCSBzRtmoLMenVbBi+9MIRaLChSW3qUY\nvzg1x9OHO8sGr/96/gPBZ/Ig0JdUUIpyWgQ3FpZIJNKsRBL4lmOAMFWrJtGObLUOZ3q4yKZtJDa+\nEgsx4b2JJ+IrzPu17A6eiI/+MnoTOw0DJRXt5dbodDZNKpMStLWRZIwp/2zhGsuKg+veKfqbe+9K\n8uZ+DWB/EfaI6xOWmUyWmno7Ncrqwm9bWl3BUN2MM+Qumodr2Ucsy3bUMlUh+QO3AuQhD1P+WQKx\nFSA3x8Y9U0WUXHnk/cm18YXr3ln+7Y/P0VynKupemA0soq3SlDz/Hfp+/tPFv11j2+3IJVfYLjrJ\nn/yXW8UumiXBpN0e4xBnrbnOI2N1c9F97pTY2yx9ZwW/OZbCcU7sa2M0eaUwN+eXS+nL9JpGzlgu\nF7prhLp38vNQLJIw6s7RMfU39RTO28j2ahRKTq2RLVh/z8UVG4vLNg5qv8avfr1EIplg13EPiYBw\nIZ1cIitorqrDKv73wz+kTSec0LhTh+nad/rKDXj7vEWwo/jaaJrtomI9WVnQjGVWWlLkAht31+Q7\nctYyVNzpmk+DB1mH66YlwNOHO/EEooRjSXpadDTVqbhpqfh8XwZUSeWcWszpJeqqapi4Fb8/uqbY\nrYJibCr5s2XLFn7wgx9w/fp13n33XR599FGMxs9W3+Vuw1jdhDXoKEmyGLXNANzwTbPLMFjS+TPp\nm6ZKpuas9XJRi3U4EeWAQQocorUMPVtrrZGWqs7CBjzv0AG0V23Nfb+qVViLSN3C8JiPyfkQbc0d\nPLzjCB+ftfKRO0S7IVdxsBBcEPytiysL9DZ+n9/u++dM+K8RSi9TLamlv36w4GCVow3YYejnvHVE\n+L7BHN3NJ1kE16MiNFpBBRV8lsjbJ4Cdx4u7a/Ib6/PWqyWbzevzfs6M2qlSyPj1pUX62uvZtVuK\nX3yNySVbCZUB5DbWbTUmHEG34FjWb7wT6SSL4QUU0lZaaoyCtn+9iDpAq6aNtFpOMB4p2y20Ppnj\nS9gxN3WSqZ0j4SsVwX6h70mWV4OF4NFW3SB/+d8WC1Rx8UQKjbxUQwG+HPZ6S30HErGUWDKGNxqg\nv7EHpUxJp66lcI4QT/aBAQMv/3qmhObt+J4Wzo87WU2kCpp62VoHuthtv0AmltG4htd8LfIbWGfI\nU8JzrquqYTkWRKuA33q8l/9w+a3CZ0L0RPlk0dLqCm06MyPOicJnG81n60rpfK3g/oMr5CnSjcrb\nLmfIzd+/NcFqPF1I7AoJJ280b/K2Zq1t2+h8V3qWapUJmzvM8T0tvHFmnngyzeiMj719ek4N2wvv\nikImoblOxVf2tfIffzpCJpPl0HZjIVkKuffp0nU3//f/cqBQcb4WDzJ9SQWlKKdF4F2KAVnkUjGN\nOmUJVatO20LaoGXSH+Gxh1TciBYHMpdWV0oSOGKRmL2mHWSyGRwhd0EDaDW1Wkim5vdxinV6E5DT\nXnNHSjV7yq3RiXQSf3RJ8PdZVxzIxMVJ2bVJkPs1efOb4ouwR1ybsFTIJJzY34ZbtszNldvrbCKd\n0yyJJKN0V3cUdHzW2uy2WhNvz3xUcn9r0ElLjQmZWEYkGS1osa2dY/m5aqhuYtR1vej6OqmR4Vk/\nV254+PUlKz/6FwfY1l7PbuMgZ61Xis7dyLan6mw017VxftxBxjBe1s/Ix0DK3UcosbdRV/WDEJB+\n0NDarCEYjmNqasEWcpTo6UBuLkjFUsKJaNG8WC+XkJ+HlhU7bTUmVuLhomSPkM+Rv384sfEexxdZ\n4qtNz/PB6RADnfXsGJLznrs44ZmHNxKgSd1AlaSKXYZBsln4qwv/vdBxlgnrODNqx+6N0N9Zxz++\nO12Yb2s7jbe113N+3EFPay0LziChaG585TqKc906sSI92XgyRptBRnOdqqD5A3furrmXHTkPqg6X\nrlqBWASpdAbfcowquQSxKHe8gi8+womoYPw+lIje+eIvKTaV/HnxxRf58Y9/zODgINlslr/4i7/g\nhz/8Ic8999xnPb67Bq2iWjAJo5VrAFDLhasNjrTtI51JFW2ku+s6qJIqsAdzmwl1GWFQlVTJ9EyG\n53ueYzY4hT3kZqe+ny5tD5PDwF4wy3sZlpS2hxplvRh6azh4JMVscIqLobN0HGzmMW0PnrncJnYj\n3uczow7cUT9JURR/LEBVtRz3ip/TI3YO7zCVpQ0Y0vdhCwSwCfCVtmjagPKVeJuh1ShHN9RZ17bh\ndRVUUEEFm0HePunrVfiSOTuWD+rkbbgn4ueGd6aw4czrBkRWU/iXVzmy04yidoW33C+XrUCD24ka\noY3M2s/zIqiZbJYthmYUyjnUMo3gutFWY6Zb187PbrxdOJb2G7ixGKC6ziX4m4WqO1uqzaj3+bgZ\ntJWcn8lmOG8b5t89/seFY3/zymgh8QOwFIzTLjVgF9BQ+DIIQyulCkEtv/41QYr1gWaFTFJI7qxF\nPJkmGElwaLuB6/NLiMUiHjmiIiKPIUvk9FSaVA2Muq9j1hoENXnaasyMuiZxh725yslooGhON6rr\nMWlMvHl2DlNtC5YV+4YVlvmNcY28uui78pztG+kNVnB/Y7dxkNenSrt2TvY8xi/+aRG1UlZI7OaD\nkGtt0Z3mja6qppCMvNP5jpCTx48P4FiUYKhXsaWlFosrRLtBy1JwtehdiSfTWNwhPrhspb+jDpcv\nUvZ9EvI3r8/70WmFKeQ+S/qSL4pGyf2Icsm8Rp0SjVJOXY0C/3Ks6G8eT6ZZCsY5MKjG7oswZVnG\n3NqKLXjbH9hlGKRRVVdka4W6JOUSGUfb9pckUw2aJp7c8ii2oBPXLfrMBpWOEdf1kmAoCK/Rckn5\nZL9e08iYe7Lk+OQDlAT5NNhoX/ugYHzOX6DbTdVYORUZxqQxsVPfjyPkLhQPjbgmONq+H41MjUqm\nLPE3hDrGAMxaAyLEDDZvJRgPFxKV9Uodjap6WmqMhbman+trNaRkQTPxZAyxWMTeh+S8tfg6/+2G\nla31nSXFrBvZdl/KhmFvFH/WQm1WgVgkLvy2PPLzPv9vIQgl9n6TOEMFnxxNtSp+cWqevQ8ZkUtk\nXLSPsNe0oyCV0FJjQC1T8f78WSA3L/zRJcEiE0fIha6qBpO2mZoqLaroCmIxhXkl5HMANKkbsN+h\nkK5BZuLFX7h5aLcMfbuLlxdP0V3XIWhDjdpm5GIZ6Uy6yK7nO86eND2LRzXHisnJgtjM3odMnLsY\n58BeBdkaO0lphPdsDlyZTpZ0E6xKnezarscg6ebln0dIpTKCHcXlunX6O+p4ZLeZD69svrvmQe7I\nuVdo0ql48Z2pkoK773x1czrkFTzYqJar+WgdI0reb6tAGJtK/rz22mu89dZbKBS5LGo0GuW3f/u3\nH6zkj1zLUz3HsQddOEJuduj7MWn1iLO5RxBORAWrDcKJKK2aFn4+/WbJxHq88zEAVpMJQT2hRCpJ\nszHAy1M/K7p22DXB1/q+AUA6mRaklEsn0zS0+fm7sdJrf2v7NwHoUPUhl5QmcNpVfXgTs7xZIuA7\nzvPdLwAmMmEdOyVPE6+x4kvaaZCZUIRbSIdr2WHaKshXOmTM8WeWq8TbDK1Go7peMODZpKpUZVZQ\nQQW/OfL2aW3yQiioM+aeLNBNjM14uTCR23Q8treVU8M2Bo64NqxAAwrdOe21ZkZcE0XnV0kVtNWY\nyWYpbIz6m7bwyvW3WE3FOWDeLWj73WEfV5xjHG07gH9lFaN0Cz97cwmZREy7xCgoaL02EAs5myqW\nZjjtOFU2kG9UtTK54Gdbe33Rc8sjnkyX1VC4X4ShP0vc8M0J/v1v+ub5ypajQGlVnk6ruFWRXgqn\nL4LTF6FRp6StK8X56M8LOit5n2KXYZA3pt/n2a0nmF+2FPkTv5r5kL2mHQCMe26UCVRO8ETzt1CK\ntiCXXClbYQm5jXGVRIFSWlV0PJyIYqxuFlyn95t3fppHWcE9hjcSEJy7vmgAaCpJ7BYHepZoVbeD\nOLVhQlspVRZRGJWjwWpQ1/Gh/2W+vv07DA/7iSfS7NnWxNZ2He+cF6a+HJvx83vf2M74rL/s+7Te\n38xXiifTmSKauN42HY/tbf3MgiVfFI2S+xXlKp87jDX88vQcyXSGg4MGnjzUjsObs7EdJi3ZTJbX\nTs2RyWSxuEI8ojEWbFredqYy6cK8X44FgazgexNNxhj33CjSXskH5sfck+iqahj33OBbfc/ykFHG\n/LK1KBh60T4iuEZLRBIkUomgrW2pMXLZMVbyPNbSjt5r3AsarjvpGd3vODPqoLFWSVtnKke367+t\nySv3yNhv3sV529VC4caEZ4q2WhMikWhTHWNyiQxDdRPOkEewYPWF/pMlen05DalDBCMJmkVbePXN\nnO18+EAVo5nXSbhy5xqrmxGLxEXft5Ftb1xDTSz3ywRp59bO+3K+iFBi7zeJM1TwyTExn9OSKVBn\n6mxYl+20VbfzsLmXN2ffoVPXVkjuLa2ucKLrKG/PflQy1050H+WD+bOAiA/mz7LHOARQNK8u2kfY\nb95FJpvBHnTSWmtCIpIQjIc3ZERorW9HsjvFDfHbpCMdhBPRsl1KBk0TY65JGjX1gu/WYvI6k8Hc\n/LW4YMp1AAAgAElEQVSHcrIQLzz7HJ7sHNFkjEA0gFgFo65JxCIRtqDzdiztFp2tUEfxRt0629rr\nC3uuzeJB7ci5V5iyLBfYFHRaBUvBOPFkminL8uc9tAruAUJlugXX0lxXUIxNJX+kUmkh8QOgUqmQ\nyYR56e9XZMjwxvpKSJeMp7bkEjj2oHBFtT3oolHZIDix/LGcE2KWbeOVxX+4VZ2bo4VLpJN8p/MH\n3IxdFbzWmpgCjmJNTnHFeblEi+gRoxqXNyh47bh3kq/2PMzVKwm2q0p5Ra9fS5Mw3RC8djZ8AzjM\ne5cspCVZJCIRdSodkpSIdCbLR1etyNvmBZNZC8vzwL7fiFbjon1E8N4X7SN8Y+CpO15fQQUVVLAR\n1lZdyUKtaOSTgnQTAKemR7hwaRW3P8beh+QktVamksM89Ggvc6FSvmvIBVYf6ThAJpMhkojxbMfz\nSLJxHm59iEgyllsz1HUMNPbyjxPFIqT5gNFV5zVW06sMOydKbP9OQz8AS6E4nmsd2FNJMpks8Uwa\nWagFuWS0ZJOztb4bhUSBLeikv3ELKqmG16Z+RSabKbsxSnr1/B9vnivQaAjZ9TPnV/ne179LSDZ/\n3wlDf9ZYWC7tmAKKeNDXV+Vt764nupoqonXIo1GnZHzWT4exhoTWVpajXCWrYn7ZwoRnqmheQI42\nRSNTsVPfT7KMVoQ7O8WFt5t55qlnsSSvU6/UCdN3iKScWrzAfvMuNPJiXYF3Zk/x3cFnuemfxbri\npKXGQHddO6/deJsJz1Sls+E+R9m5u2TlyI6dvHF2oSixm+sEvIpGruKg+jl+9eYyJ45XI5cMl8wb\ns9ZAlURBs7qBnYZ+lmNB2nVm6qp0gh1rComCcCLKjcgw6roObJNRLO4Qlyc9PH24kwWXsC/Z11HP\nD785xC9OzQm+T+v9zbWV4mfGHIVAgFIh+UwDJ18EjZL7Gett7JaWWpKpDIvOlcLf++NRxy3KQCW7\ntzbj8kc4N168pzt1Nsb3v/4dnEyymrrtD5y3XUUukbGlrr2gq7YelhVh7ZW1hSCJdBLfqo+3pj8o\nCYbuN++ip2YrsowGR9RKi6aVrU2djHrG8EUDnOg+ijcSwBZ0Yla3IA+3EYq7Be22Rqba9LO7mx1p\n94qG627oGX2eODNqR6OUF9b49V1gEpGIb/Wf5JXJtwp/22Q6iUwiHFPxRZZ4pOMg1z1TmKoNdOra\neO3mr+ht6BS0O9OBhZJ7JNJJIqtxRj7QsxpfYl+fnsuTbkR1DhLu20mleDrOqGuyqOOjUV3HYFNv\nWdueP1YuUbW2SKCcLyqU2KvQd95bzNlzz3o9deZClQzp1gyrqXjh7wfQpGrAGxUuMgnEltmh7+es\n9UpOiD2bQiGWc6L7KPagC28kgL66kWqFmkQqgVQiJZFOcsl+mf3mXYJzxKw1oJAosEQWEdeKUMdU\nhU6ytcUrvsgSJm0zIOLtmY/o0rV+IlrurGqFy9OlHf8nuo8WxpVIJ3GmZ6mvaRHsKK5069xbOLwR\nDm03kk5nSKQytOu1SCRi7J7w5z20Cu4BysXvy/lzFWwy+aPX6/nRj37EwYMHATh9+jQGg+EzHdjd\nhjVoF07CBHPt5c2aBsFqg2ZNA86I8MJhuUWnMzkBT/Q+izM9gyPkoq+xF4Okm6BPjS1dWuUCt9tf\n3XFbYSxr6QC0GjkzrnITOnftgjOExV3KK3p8D9hDuXPWO57547LqZS5Gblcl5c89Xv8C495prEFH\nSVCyVWsCblc1AIUse/44bFwd1lPfyTuzp0rufaLriOBvraCCCir4JFhbdXXm/CpPHX+WG5HbIuBr\nKeBurFzHoAzRNdDJa3NvshrI2TJP1Et/Y4/gmqDXNHLZPopCoqBD18p0OBfA0Vc3UaesxbJsZ9o/\nD1C2krNJ1VDYuORtv1wio1ndwHIsiK6qBk/cRl/HHgKh1UIb++yUmN39zyBqsGBZsRWS5/848UtU\nsiq+2X+Sx3uO8a/e/FGhQm89fUOTvAXxsokz51fJZLIFGg2hajWZRMyAfgt9HV++9um8TmDJ8Vs6\ngXmsr8q7Pu/n9IijpOqvSi4lnkwza19GVV9KawO3NaTynRtrfQIAXySAK+MFQCKWCN7DFrHy2OFu\nXnp1iaOHtkJTiK9tPcHCkhVn2FOYM/kKXXvQxSHNc7iYwpew0yg3oU22455u5F+efJTFJRt/fvqv\nOWfNnT+3ZK10Ntzn2GjuDhkaeOPsQlFi97p3FoPSjDrWhsMi4enDncRCCU50HcUZ9uAKe2lU16Gr\nquHd2dOspuJ06VrZru/DIXYz7V+gQRXkyS2PYg+6iubZRXtOQ9IRcoLCyaH9+zl9NkY8mca7HKVa\nJStw6EMxRdu29nqyWbh03X1HGjehzkWXP8rYjP+uPVchfBE0Su53rLexM7Yl/p8Xh4vOyVEGhmmo\nVeFbLu4WE4tFHBgw4LHJULRVCSZHV1bD6KsbBTsTmstQsPkiAfYYh5gJLLC9uQ9PxCe45qdTIv7H\nS0GeOrif6tVdTN4IENHJGRjYy7LKyoTrJl31HRxv3sN/f9mBTLLKwyck7DXtIJKMFhXKSUTiTT2z\nu92Rdi9puB5kPaNFV4hUJkN1vaOEEqu91ow77GM6sFA0Tzbq0G1Q67AFnLQun0QZE3Mq+Euq5ery\nNJtBVwm9IIA1bOXIgW7e+XAFpUJCh1GLI3r7HcrTu+ULAdbu0ZdjK4WE3KRvliZ1PVKxtGDb8/BH\nl3mm9ytcso8WknYA1XIVN3yz1Cqq+f29P+C6Z+qOib17qXVSAegb1MJFS7VKzl8I8I2nvoc1Ps3X\ntp7AsmJjNZUQnK8Ai8t2kreKSoBC8mWrtIuh5m3EUnHml3IFTiZtMx21LczcSlqu368Yqptp0ep5\nb+5jgvEw5mojdSpd0Tuzds5uqWvHE/Yxd6tIazqwUPbd0msaitZpuUSGPegUtOHOkIcmVQO2WzE0\nR8jJv/2fv0m7sUbwGQjtC/7mldHPtGvyy4q9/U24/FFWEznNn0adErlMzN6B5jtfXMEDj83u1Su4\njU0lf370ox/x93//97z66quIRCJ27NjB97///c96bHcV7rBvw+NmrZ4x96RgtcFSOFr4/9pEilGZ\nc0J0zVHeEqBYe6Lp25jEzYKLTr51v7W6VVBfJ55IY6oWvtaszSXeWvXVWNyhEl5RsQhatEbMWkMJ\nF6sYEQAR5SKJoEDFhmiWVk0H1qCjJPhkuPV7+zrq+Ze/084F2xVsEQvb1K3sM++mr6P+jtVha1v6\n8/d+kFr6K6iggvsba6uuxmf9eB1yTF2tBVsqRJc16h8u4lZPpJOCgs55wdNAbIX95l1FHO3WNdRd\ntqBzQ80MRNBwi+t/vR5R462NNSkZkze8HNmV0x+KKhfxJx3E5Ea61M3MLy0WdYWEE1HmbwW1zOrb\n68rajdEB/WHOvK0mFL0dHMvTaFSq1YpRrRDWZMrrBJZD0fyb89NYq6RKLuXceG7+9bTUEpUasZah\n75v2z5flMG+4RaGy17SDSCJaloolKlqktclINpsmlFzhhsVKa62R/qYePlo4z2oqXji/SW7m6pU4\n7kCuiMQWTrCvrwYUaf63vz6NYfscgdhK0XdUOhvub5Sfu2puWnLvu0wixqBsQbZUx+q1Zs4HosST\nQSDI2IyfZ492YQ+EEMlFJNPJgq0Ri8TsN+9CLBJxyT5Kg6oOs9bARfsI171TnOw5jjPsKbJNcJv+\np6HGhkLWRDyZZsEZ4v/63QO8d9FS1uZs1i59XpXiXwSNkgcJ1+f9nBm1o69XY3GVBis1ShkiEUWB\nzAMDBi5P5gKQB+pTGG/trdavvaYy+0CDpkmQgq1BXcdZ62US6eSG3RuOiB2looUpyxLXZv23igBW\nGLkp4dD2Nk727+PhIRN/8B8+5KHdMpLVFmZCTprUOuqVOvyRpQJ11h8f/YNNPae73ZFWoeHaHFr1\n1Vy67uZQ0yDvzBezjVz3TnGs42AR/R+U10DJd9dkUPHxqIP9AwYaqo1MroyWDWibtHqGneMlx5vU\n9ag0y+w87mExOUyLqRW9ZgeOsItMNlOSgFq7R++p7ywk5F4ef4O5JWsJvRtAl66Dbw4+zTcHny46\nvn6+HWjdfcfnWPFH7y1amzWMTkkQi0UceVjJimweX9KBStPKia5u/u4VD8cOG3jN/VqO5k8i21Dr\ndO0cz//fpNWzHA+VsvBIZJzoOoplxVHYr1RJFRxt308oHuGifZROXRtVUgWJmBRRSvidSaSTLK7Y\nGWoaLCR/Nnq3aqtqChreF+0j6KpqcIW9gs/HFfZyK3wG5PQvyyV+1qNcXOwPv72T8VlfJSH0m0Ik\n4sKEu0Tz52tHKz7YlwGfdq/+Zcamkj8KhYJdu3bxu7/7uwC8//77yOXyz3RgdxtGrV4wM2i+lYSJ\nJGKC+guRRBS9eAsHW2JEk7FCIkUlU1IVbAcgWiaR4s5O013XxfA6LQi5REZXbe7a+kw3ckmpvo58\n1ci2pmbBa3vrciJmB7cbBSsid25tJqbu4e9GS8XKf2voeQCcMWFKI0fMxi7VceSSiyXfq4q1AbmK\nsr8Z/q+37x1ycNV7hXrtH/DR1ciG1WEPekt/BRVUcH9ifcfhI7vN1GjkvPrBLPtqjQW6AiEKOCHK\niov2EY51HGIlFMcVt6HX1FOn1HHNfQONXCV4n1QmTaO6jnQmTZbshhsjs9ZQSBYJiUz/s8EX4KE5\nfFUurvjOk4jd+hwH15dlHG7dy2nLxaJ7zwUWAdhn3l2i2wYQcdcUJX6gODha4Za+jXhKWMtvbeKk\nHPLPcdq6xJ/9fxeQSSXIJGKQQGQ1hTwoTN+Xp8hSyZSCzqxSqgQgkoyWTU4qpUosK/M89JiSd2Y/\nKvD5225xmq9NcsolMozSHi4Flogn03iWYjx/sh5LYgR70kH3UA+zYWFdlkpnw/2LcnM3nkoizmZ4\n8mA73eZafvzaNfra6wUrfq3uEJJqI3KDtUi4Xlhr6rbegzcSYHnN+XCrkKo6R9viCNn56iNbeOPX\nS/R31LGlRceWFt2Gv2czdunzqhR/0DVKHgTk1/ZMFj64nPsbH9puRCGTlPy9u801zNhXCp8pZBJW\nEyniyTRisQi90oxYHULuKl17HSH3Gh0KFw1qHUqpEplYJmhrq9bQXkWSUfpqhYOhhmo9zlgSz1IM\nnVZRKNaLJ9OsRBJ8dMVGQ20VDx+s4hf2V0ks5d+tnM1+YssxRBkp4mgD//Xv7Rx51Mls+Ab2kBOz\n1sCBll0lAfW73ZFWoeHaHA5uNzI67cUb8Qj6mZFEFJNWXzJPLtpHeHbrV1lYtuGJ+AudlpcdYxzV\nPYujLk50NcFgzSCTK6NlA9q7jYMlyR+5RMa2xm7+aeKNon17npIwn8DcDC3bedtwWU1AAkauz/uL\nbPWdqAc3YgrZyO7fC/2pLxMMdSq+/lQdWY2ft2ZvFzPntHCu8MJzz+FIzZCw3060bJSwzCeImtQN\nqGUqEukk3rCfbBldNW80UEQ/vEPfzwfzZ0v8jG/3fpNwUIJba2XENVHk57RpWznR8zCnR+zIJVeL\n9nL7zbsgK8EWtFGvrkUhUfD+/Fky2UzBfxn33GC7rr9s0fVV57XCb/wk+pfluibfv2QpFAN8WhrN\nynsAi86Q4PMVWq8q+OKh/H4n8XkP7b7FppI/f/Inf4JOp2PPnj0AnD9/nnfffZc///M//0wHdzfR\nVmNkeI2TD7dFNQEiyVUy2QxSsZR6lQ6pWEommyGWjJPIprjsFOAAbdwKgKNMIsUetbI9tZMX+k8y\nE1jAHnRh0urprmtHFK4F4OKlBNs7TpJtcJIUh5BlqhEtG7h4KcH3vtEkeG2tPGfY62uq+NqRTmye\nMDZPGHOTBnOThqa6Kt6w3hRcYMc9N/nqliO0aM2CybBWrRm/TcF2aamWUNiXy6JuVFE2ZTUKPou1\n1WEPckt/BRVUcP9ho8qqHETsMQ6hkMqY9i8I3mM9/3MmmyG2mkLq2s4e0zZW5FMsrwaRiCUFqpf1\n2GvawdszOQHUctzV25v6bgVBXZzs+QqOkEvQnt4ITDPmm2CgqVfw82gqxvbmPqRiCRftI2SyGRpl\nJn788zEODZn47b5/zohnGHvUiknVwmD9ED95sdjmV2g0yqNOVctb0zm6wDz9CcATW45t+h6ehJ3B\noy7sEStdChNtVds4ezaKZfKWqO6tNdZcbaJZ08CoZ4ydhn6y2Sy7DYOs5je1NWbaalrwRX0cbT/I\npHcKR8hdws1fr9TlEos1BuwhYfqKDBk6alvQqwxUhdsRRXXAEgBHDip52/uPheu8t+gPbQK+QqWz\n4f7FRnP3e18b4sain5feneLgoJFrM6Vd8TqtIudXTqzy8IFWvtrRgCvqwB/NCehulDyfX7ZyuHUf\noUSYheXb1JRvTL+PVCy5JQb9c44cfJyjO+6e7fm8KsUrBU2fLfJrO8BAV31hjT837uTAgIHVRArv\nUozmOiVymZQX353i+Ue7aNJ1MO8Iks2CdylX8HBofxVvO37BLv0g3+w/WUK/lclmOGu9zNH2fYjF\n4kL32jO9XxEsDsxms4Vr1TIV2jIVqNVyNWqlrKD7thbepRhNOiUjN70EtLOC75ZlJUcluzVzgt0H\npLw880rRfjQflFybALrbHWkVGq7N4fAOEyLgVccVwc/tQRc7DP0l80QqlpDMpKhRVNPb0MX8kpUp\n/zz9TT1IlAH6BjV8dDrA+Bw8/9zXmYtNcKRtH8FEGGfQQ7OmgcNteznQuptwPMo1z2RhrqplKq57\nZ4T9gWyGh00HmF9ZZDUm5QnTs1jCC/hSDrp1HRzr2ldky7Y2dPHe3MclvodJ3cLrr0QhepsG8E7U\ng59WR+pe6U99maBuivDTsVfYku0QnCe25A380aWi43mKtlQmhTvsw6TV01JjxLbi5CudD7MSD+MI\nuQknouw370IlUxYosdfDFnTyePcxFlds+NZQYq8fx9TSNGKkgIjtzX1o5GokMSW7VbtxLsjwaZQs\nu1Ucqn+OiHIRZ9RKncxEwmnmxmSWA49V85Hto6J75//9O0P/EzZ3CLlkpLT7s7qJpmADLTVG9pt3\nbqp7LY9yXZNCxQCfhEaz8h7k4PRFPtHxCr5YqFfpeHP6faB4v/Pklkc/z2Hd19hU8mdhYYE//dM/\nLfz/3/ybf/PA0b5ZVhyCmUHrSi7D36xp4I2p9wAK1G4AX+t9HGdwWnARCkhmgUOY1K3CiRRNK/5Q\nhF86X0cukdFWY2LCc5Nh5zhP6r8FQIdJSwo/mWyaQGyJRrkKCdDbWsOwe4QPFj+mWdPAHsMgl53X\nuGAb5ljbwxzqGuCjqzbePLtAtUpGu0HLtVkfZ685MTWqy3Kx5o83KOsFNykNyjq2bjfy53/rQKMy\nMtC5nfE5H+Fogj/8di6xs1FF2Z6tO5ixLpd8VqkOq6CCCj4rlKusGp/18ae/d4C3Fl/nrPUyGrmK\n3vquTVEVyCUy0j4D58acnKiv4VJgtFCV5on4bgXFnUXn57uB5BIZi8u2QsDIFwlg1ppQy5XccFup\njvVwUH6UsfNegi3DJWMBsCzbGGjqLStamF+7PBFfoRrfIO3hpdPzLIfiXJhwAw3otCbOBeMMK1z8\nr9/fzciUh7EZf4VG4w4Ydo4X+Qz9TT0oJApGnON8b+i5O14v1CE7LhnhxN5vsfCLYlHdc8E4D21r\nZuvWFB9YPyxck6eaTWQS/GLqVzxUdZJLVxIMHDVjCzpLuPn7m3oIJcLUKWtLqGXycATd1Cg0iLJS\n4ss1vDMyy9MPd+DyRcjqJgsC0LAx/WGls+H+xZ3m7vlrLgLBOBKxmEadsqTzZykYZ29/M4lUmgsX\n43BRQnNdD0cO1HAh+Kbgd+aT543qOk5bLjCk7y+iiwNIpDMFPSuV2XPXbc/n1blYKWj67JBf2/X1\nqkISB3LC5GfGHChkEvo766mvqSIUzXX4BIIJrs36cPujNNcpaa5X4w5ESWqtrAbinLVdxhIU1l0D\nmA1YSKaThbXcEXIz5p6kSd0AWQpz+iHTEGatAU/Ex9LqCv7osuA+0x+ME4klC7pva9GkU9JpqmHW\nvsJSRjgw6o0EUMtUpBU2vFnhoOh523BRQPJud6RVaLg2h+vzfv7zz8bY+agwpXu7zswVx5jgPBl1\nXae/sZdXrr9ZUmy6xzjE0ye2YpmVMh+8zlRwjrYaE86wB5lYxph7kgaljjplLdP+OSY8UwW/QFdV\nU5aS0BZ00lszQGLiEFcDUc4lQyhkTRzZsYMLlzwc/Wc6aLx9fn5erfU9pv3zSLw9xOKxokLPO1EP\nflodqXupP/VlwWXnVdQyVVm6alfYS3ddO/PLt4ud8xRtuxv2I545gmqfleuem/Q19vDazXeAXDzt\nujfniz7T+1WMWmF9DrNWzxXHGE3qRh5vP8EvZ4X9DFvECllIZpKMuHIdbjslT/PTjz0AnL/mYv+A\ngavDKSKxJnTVrahbapmY99PSpGEycLFkTgLYVlwcONQPnTDobRAs5vjO9q99gid6G+W6JoWKAT4J\njWblPcihzVAt2L3ebtR+DqOp4F7jqvOa4H7nqvMa3x169vMe3n2JTSV/VldXWV5eprY2163idrtJ\nJB6sdip70FnQZMg7RIl0khZtLqFxxTEqOHlmA/N4o8LG2BLK0aH0Vvdz1VNK3danG2TYnasgSKST\nTHinC5/b4lPAITq707y8+DoJ/21KH7lkhO9s+S0+dM8XBCNH3TcwaJrpqG1lbnkBuF1NIJeJqdNW\n4fCFARi+6cPUXtpWDmC6pRc06hF2Pkc81/je48/wO981ci0whiN6iQFzC4N12zm83QRsXFG2q6GJ\nn304W6kOq6CCCu4ZNuKj/71vDPGTydyGJZyIIpMIU7i0yvrI1KjwJ+3oq8w0i7vxBGLsPO5mMnW1\niBsaoEnTUERToKuqwR9dKhL5jSZjaOQqRCrQVmlYWQ1yyT2CVHyFo237aRmqwp8oLzKtkSvRa4Q/\n12sacYW8t6o3YZf0GeanxVSrZERWUwUb7FmKcWh/FclqCy8uXKalrpXvfWMP+zv6f7OH/gWHSavn\nnPVqic9woGVzFX/vz14QDHx4stNUq5oIRZMFvT6FTMKW1lpO+39VUpHojviQSWSoZSoiykX2PdRB\nTJItzOH8OXKJjNYaEwqJgnPWK2wpoxtk1DYjF8uwLi+yPK8nlcpwZdLDN4518br3nZLzL9pHONZ+\niNV4ClvEUulseABg0ho4Z71Sdu6OTHnpMGqZsizT0lxdRJ8lFos4sE+BuOE6mnoL7VIDslArl66s\nspiwFbTK1iOvV6WQKFDLVCwu20pExyEXbNRV1TC3LBzorqCCtciv7UvBOANdpRSF8WQakQg+uGJH\nLBbx9Ue6CQRXMTdpsLhCWNxh9vYbcPuj+JK3g47LqyubKgSpV+qordLS19iDLxqgQV1HS40BEJHM\n5Gx1XlNVIhZzyT4KFFegPqX/Dr2PNvCP7xYn5BUyCQq5FKcvgqFBRXOZvVV+PDKxnfpkreBzsq4U\nB1Q325F2J1qutajQwt4ZH121MdDZgGZVJUjpnkqnyvoWh1ofIpqKCvoNsVQMZ2oGp7+FwUEF3dIO\nVlaDbG/uI5VJcdZ6hXQ2w3+5/A+Fa/L2N5KM0qstP9dnV26SSO0prAHxZJqblmUUciljM94SWqk/\nPvoHvDV5FktoMccMEjdz5vwqUFzoeSfqwU+rI1XRn7r7sIQWS3Sf1qJRXUcqkxLcO7UoumndKcYa\nDxFNrmIJ5oqt12tOO0NuahXaonvkqeGkYinzy1bml61MeG/QX9dfkjwVi8TsNPRjW3HiXXPfeMxG\na3Mr3uVV9uyWka0bQ1Nno0NmpE3TgWN1FE2NDZWihVqFWTAp26JpK/z7bhdzlOuaFCoG2N69efta\neQ9y6G3TcXGiVAKjp1V4razgiwVDdXNJIWSefaUCYWwq+fP7v//7nDx5EoPBQDqdxuPx8Gd/9mef\n9djuKozVeqxBZ5FDBDktIIAmdUPZydNW3SZcqaBuAWB8PMt21UlSdTZ8STsNMhPSoBnbg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//nX8FR5d8yBEYT65gEnTWMW/MPID9z/zeOuzfOu5onD235z/nuhasLx7p1pH2RpjK+e9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\n+GoByBPTZz+SJkUNNdTw+cb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eWMOkd5HQwhJbe80EwgleP3EDp0WP1aTBHYiVVWpDcS5W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\nN4iXPkMkJ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mYZjzYF/n2OmH7nohZH0z+ApbRR6Eyj2C7y35FiRzjr6PWbwwFtB3zf7/Kn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gJ4+w9GKPNK0LSpCb1XrDg9ZcU928Kzhg7cK8Gv+v89+tSxb2IAXaZrePbeP4dpjI8/nB1O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\nv/46jhw5gvb2dgDA6Ogovve97+HNN99c8jH1e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RERERERERERERERUeiCWvnz4x//GHK5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\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OfjjxI4G33xPz8pH7FC/1P8Vmy8ZbSr48ubeDD0a8NXQvn9vTftOfcbcgNon9STWOPg3c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kqnQHqND3iLgxtNaVbrhebwVDU24q86sy7m84Fsl5r6q0Rj60n6eptF7w/WrldiLVUpzeZYIr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\npew0cAxPqnEGCsBSchFje4foa970Ut29i33Wwc4+3po91bBZn+w5DNyd+T1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79znPGN8b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IjbcHRU4vWmsznBg6VMLs9bk15Bhnrsgo8H9zjpsmn5yVsh4JrlO+R47hO6WuihjW3jqRwA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\nxh7C6ZVarG633o5Vbeas/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Is5VtIRQTrb+G2vVw+o/u2LB1vq6dWyzXShqtwaTke2nC8G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\n8b2ftsNqdy/5PDJuWnX9SUQUj4Ta9jmSbGwp3eTXrpi1WVCaXSpYZ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RZzjjnBeJqXjaJS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\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95kNMR8YxyWy0aTrIyWPstg7giwVp1zlI+a18dHwFmUTMPpVVkEorl5GwS/4McpOP2eVZ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ZkKz1Qp5+/8fDhVtlM3++nnPCMctO9mwNjDewvnao4767nMQftubCobsUwcmVjKlcB43VpasUUp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\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iiCP6pc3my3io/DMwjdoiVh+PmOQ4WLwbNtfY7S2LVbnoHTNBKpGiPi+w+9D8+hUI7AIT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\nhpcTqZ8pewdIX1s/3WvqIhFpBFpJkei2rs9X0T/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AD/99aeyoywK4NJVaw/3euz4PppcL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jq/NDWBs3JLJJitIkgcUUl2fD/Ne/O41aKSMSXakwpv/jr3VVMYYa7fb9R5mN9uzD3RXWYItO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o36Pi741nEkNTMPRztrCgt1t3kpiqOejzOt/pqE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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f4529e84748>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import seaborn as sns\n",
"sns.set(style=\"ticks\")\n",
"sns.pairplot(main_file, hue=\"Outcome\")"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "99ed7d80-25c0-4d98-858e-67c60049e5f9",
"_uuid": "7922851c7a0d715a2a47bbda5c02f6499c201ffe"
},
"source": [
"###### Separating the data into Train & Test (80/20 split)"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"_cell_guid": "7bb57036-fc0a-411f-963c-6c8d336cb919",
"_uuid": "7e017d406154538d0d869ddcf0e888668dd49120"
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py:1: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" \"\"\"Entry point for launching an IPython kernel.\n"
]
}
],
"source": [
"X = main_file.ix[:,0:8]\n",
"Y = main_file[\"Outcome\"]\n",
"from sklearn import model_selection\n",
"X_train, X_test, Y_train, Y_test= model_selection.train_test_split(X, Y, test_size=0.2)"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"_cell_guid": "6794db29-23de-4b37-baff-bbab6278ff18",
"_uuid": "adab9b70d1e6278775f9f7d678c0128a43bb65c2"
},
"outputs": [
{
"data": {
"text/plain": [
"614"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(X_train)"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"_cell_guid": "f24c0e62-e3c7-437b-a5ef-317be9e581d7",
"_uuid": "d0eddb2629c035a28520d7f484489904fda4c9d1"
},
"outputs": [
{
"data": {
"text/plain": [
"154"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(X_test)"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {
"_cell_guid": "7c2bfaf0-ad6e-4b45-8ecc-bfce57327079",
"_uuid": "ddec54509776d54e966439fc98ed3fda12fdde8a"
},
"outputs": [
{
"data": {
"text/plain": [
"614"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(Y_train)"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {
"_cell_guid": "af4202a6-b69e-496c-93ef-7d816a3e1e2d",
"_uuid": "3fd70584f6f806e8a7848aca03e3446e602f69f1"
},
"outputs": [
{
"data": {
"text/plain": [
"154"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(Y_test)"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "e6b40d33-765c-4bfe-b448-0665106fdfd1",
"_uuid": "625df4928b1b1aec5a75b6dc3651d5a133955724"
},
"source": [
"###### Importing different models to check for the best accuracy "
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {
"_cell_guid": "1cb5360f-4fc0-4d68-8408-b37b5d96f01a",
"_uuid": "90ff12fc57aa32d76a69ea3f79d97cbb9a4ff6b6",
"collapsed": true
},
"outputs": [],
"source": [
"from sklearn.model_selection import KFold\n",
"from sklearn.model_selection import cross_val_score\n",
"from sklearn.linear_model import LogisticRegression\n",
"from sklearn.naive_bayes import GaussianNB\n",
"from sklearn.neighbors import KNeighborsClassifier\n",
"from sklearn.tree import DecisionTreeClassifier\n",
"from sklearn.svm import SVC\n",
"from sklearn import model_selection\n",
"from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n",
"from sklearn.ensemble import RandomForestClassifier\n",
"\n",
"\n",
"models = []\n",
"models.append(('LR', LogisticRegression()))\n",
"models.append(('LDA', LinearDiscriminantAnalysis()))\n",
"models.append(('KNN', KNeighborsClassifier()))\n",
"models.append(('CART', DecisionTreeClassifier()))\n",
"models.append(('RF', RandomForestClassifier()))\n",
"models.append(('NB', GaussianNB()))\n",
"models.append(('SVM', SVC()))"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {
"_cell_guid": "ffddebc6-156e-46e8-be0a-a56eaa1c2cfc",
"_uuid": "66f2d853f3f24fef551f3dda3569bc67eab6ab19"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"LR 0.762136435748\n",
"LDA 0.771946060286\n",
"KNN 0.706953992597\n",
"CART 0.672712850344\n",
"RF 0.758937070333\n",
"NB 0.750925436277\n",
"SVM 0.661210999471\n"
]
}
],
"source": [
"results = []\n",
"names = []\n",
"for name,model in models:\n",
" kfold = model_selection.KFold(n_splits=10)\n",
" cv_result = model_selection.cross_val_score(model,X_train,Y_train, cv = kfold,scoring = \"accuracy\")\n",
" kfold = model_selection.KFold(n_splits=10)\n",
" names.append(name)\n",
" results.append(cv_result)\n",
"for i in range(len(names)):\n",
" print(names[i],results[i].mean())"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "7462997e-9388-4d65-a0d3-bb00efd7ec34",
"_uuid": "111d3db5c075fb78d1fc1d25d8757656ff7ebd7a"
},
"source": [
"###### Visualizing the different model accuracies using a box plot"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {
"_cell_guid": "c6de5309-07e7-4a4a-aa0b-42f0a9f0e41f",
"_uuid": "27a2f0c79bd84bc6a8fdc39a003fc6a7ffb496f0"
},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.text.Text at 0x7f45140c0be0>,\n",
" <matplotlib.text.Text at 0x7f45140ac358>,\n",
" <matplotlib.text.Text at 0x7f450f2b36d8>,\n",
" <matplotlib.text.Text at 0x7f450f2b8160>,\n",
" <matplotlib.text.Text at 0x7f450f2b8be0>,\n",
" <matplotlib.text.Text at 0x7f450f2bd6a0>,\n",
" <matplotlib.text.Text at 0x7f450f2c3160>]"
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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If0BXGRnm/EADAPA/RoY5ApvValWrpV6T7vN3JV1XvlGyRlj9XQYAw3E2OwAAhiPMAQAw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\ngg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f4525bf23c8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"ax = sns.boxplot(data=results)\n",
"ax.set_xticklabels(names)"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {
"_cell_guid": "19883700-f0b6-466c-b91c-0897a6859c07",
"_uuid": "c04dd0c7b857ccd43193b22c514457091fa68062",
"collapsed": true
},
"outputs": [],
"source": [
"#FITTING THE LDA MODEL ON THE TEST DATASET\n",
"lda = LinearDiscriminantAnalysis()\n",
"lda.fit(X_train,Y_train)\n",
"predictions_lda = lda.predict(X_test)"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {
"_cell_guid": "572cdd26-3944-4f08-9dc1-c81d2b4964a0",
"_uuid": "9769a94c691b46c7a7d3edd48866eed4da639300",
"collapsed": true
},
"outputs": [],
"source": [
"from sklearn.metrics import classification_report\n",
"from sklearn.metrics import confusion_matrix\n",
"from sklearn.metrics import accuracy_score "
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {
"_cell_guid": "a36a452a-5ead-4537-8acb-984241651177",
"_uuid": "5184145620809379b9f776add950ae5acb1059b0"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Accuracy Score is:\n",
"0.733766233766\n",
"\n"
]
}
],
"source": [
"print(\"Accuracy Score is:\")\n",
"print(accuracy_score(Y_test, predictions_lda))\n",
"print()"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {
"_cell_guid": "24bc7193-2b6c-459c-be95-46999243cbb2",
"_uuid": "0b788a10ff3aa9c63d8d50d4efb03447fdcf69fa"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Classification Report:\n",
" precision recall f1-score support\n",
"\n",
" 0 0.73 0.89 0.80 94\n",
" 1 0.74 0.48 0.59 60\n",
"\n",
"avg / total 0.74 0.73 0.72 154\n",
"\n"
]
}
],
"source": [
"print(\"Classification Report:\")\n",
"print(classification_report(Y_test, predictions_lda))"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "9aaf592d-f2c8-406c-adcc-405423ac0eaf",
"_uuid": "a41a7b2c42279fabf1164cf796598308ba54ec8d"
},
"source": [
"###### Creating a Confusion Matrix"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {
"_cell_guid": "82e887df-c343-4e95-96cc-e8afc508fb13",
"_uuid": "d2b74eb4b5da2ff8a79a0a9add05c3b905e1cbe8"
},
"outputs": [
{
"data": {
"text/plain": [
"array([[84, 10],\n",
" [31, 29]])"
]
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"conf = confusion_matrix(Y_test,predictions_lda)\n",
"conf"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {
"_cell_guid": "42018867-ef87-494f-8c27-62a8afa43fa2",
"_uuid": "4cf726930a950540bfb60c49475713e35dcda572"
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7f450f2bdd30>"
]
},
"execution_count": 33,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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"text/plain": [
"<matplotlib.figure.Figure at 0x7f450f282630>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"label = [\"0\",\"1\"]\n",
"sns.heatmap(conf, annot=True, xticklabels=label, yticklabels=label)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.1"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
| 0001/479/1479749.ipynb | s3://data-agents/kaggle-outputs/sharded/034_00001.jsonl.gz |
{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "e163d289-253b-0d9c-34c0-27818d239dd3",
"_uuid": "43dd3c0e6c79f0e761653dd549cd1f2d0b4566f0"
},
"source": [
"Titanic: Survivor predictor"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"_cell_guid": "307addaf-1389-c77a-f6ae-81d4bc1bd3f5",
"_uuid": "3b2bd48cf64a2f87f3b26bd226541365d17bf8ae"
},
"outputs": [
{
"data": {
"text/html": [
"<script>requirejs.config({paths: { 'plotly': ['https://cdn.plot.ly/plotly-latest.min']},});if(!window.Plotly) {{require(['plotly'],function(plotly) {window.Plotly=plotly;});}}</script>"
],
"text/vnd.plotly.v1+html": [
"<script>requirejs.config({paths: { 'plotly': ['https://cdn.plot.ly/plotly-latest.min']},});if(!window.Plotly) {{require(['plotly'],function(plotly) {window.Plotly=plotly;});}}</script>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%matplotlib inline\n",
"\n",
"# This Python 3 environment comes with many helpful analytics libraries installed\n",
"# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n",
"# For example, here's several helpful packages to load in \n",
"\n",
"import numpy as np # linear algebra\n",
"import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
"import seaborn as sns\n",
"import matplotlib.pyplot as plt\n",
"\n",
"# Import statements required for Plotly \n",
"import plotly.offline as py\n",
"py.init_notebook_mode(connected=True)\n",
"import plotly.graph_objs as go\n",
"import plotly.tools as tls\n",
"\n",
"\n",
"from sklearn.ensemble import RandomForestClassifier, GradientBoostingClassifier\n",
"from sklearn.linear_model import LogisticRegression\n",
"from sklearn.metrics import accuracy_score, log_loss, roc_curve\n",
"from imblearn.over_sampling import SMOTE\n",
"import xgboost"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "eab8782c-f9b5-860c-f57c-204fb9715d4c",
"_uuid": "afc12f517b139ee364b3e56b5e612f74e297c45d"
},
"source": [
"Load data and explore it. See if cleaning is needed"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"_cell_guid": "4c5bb2b6-e121-c72e-6932-7a5b41e8a8c7",
"_uuid": "183d57b56c491993bb1969b63d669d0d5fa20050"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"There are 891 observations and 12 variables in the train dataset\n"
]
}
],
"source": [
"train_data = pd.read_csv('../input/train.csv')\n",
"print(\"There are %d observations and %d variables in the train dataset\" %(train_data.shape))"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"_cell_guid": "0ec73556-1fa6-2dc5-765f-29f519362dfe",
"_uuid": "4c89586316d0009b1e0b745814246d5e1fa39b0f"
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>PassengerId</th>\n",
" <th>Survived</th>\n",
" <th>Pclass</th>\n",
" <th>Name</th>\n",
" <th>Sex</th>\n",
" <th>Age</th>\n",
" <th>SibSp</th>\n",
" <th>Parch</th>\n",
" <th>Ticket</th>\n",
" <th>Fare</th>\n",
" <th>Cabin</th>\n",
" <th>Embarked</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>Braund, Mr. Owen Harris</td>\n",
" <td>male</td>\n",
" <td>22.0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>A/5 21171</td>\n",
" <td>7.2500</td>\n",
" <td>NaN</td>\n",
" <td>S</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
" <td>female</td>\n",
" <td>38.0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>PC 17599</td>\n",
" <td>71.2833</td>\n",
" <td>C85</td>\n",
" <td>C</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>Heikkinen, Miss. Laina</td>\n",
" <td>female</td>\n",
" <td>26.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>STON/O2. 3101282</td>\n",
" <td>7.9250</td>\n",
" <td>NaN</td>\n",
" <td>S</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
" <td>female</td>\n",
" <td>35.0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>113803</td>\n",
" <td>53.1000</td>\n",
" <td>C123</td>\n",
" <td>S</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>5</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>Allen, Mr. William Henry</td>\n",
" <td>male</td>\n",
" <td>35.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>373450</td>\n",
" <td>8.0500</td>\n",
" <td>NaN</td>\n",
" <td>S</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>Moran, Mr. James</td>\n",
" <td>male</td>\n",
" <td>NaN</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>330877</td>\n",
" <td>8.4583</td>\n",
" <td>NaN</td>\n",
" <td>Q</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>7</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>McCarthy, Mr. Timothy J</td>\n",
" <td>male</td>\n",
" <td>54.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>17463</td>\n",
" <td>51.8625</td>\n",
" <td>E46</td>\n",
" <td>S</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>8</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>Palsson, Master. Gosta Leonard</td>\n",
" <td>male</td>\n",
" <td>2.0</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>349909</td>\n",
" <td>21.0750</td>\n",
" <td>NaN</td>\n",
" <td>S</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)</td>\n",
" <td>female</td>\n",
" <td>27.0</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>347742</td>\n",
" <td>11.1333</td>\n",
" <td>NaN</td>\n",
" <td>S</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>Nasser, Mrs. Nicholas (Adele Achem)</td>\n",
" <td>female</td>\n",
" <td>14.0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>237736</td>\n",
" <td>30.0708</td>\n",
" <td>NaN</td>\n",
" <td>C</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" PassengerId Survived Pclass \\\n",
"0 1 0 3 \n",
"1 2 1 1 \n",
"2 3 1 3 \n",
"3 4 1 1 \n",
"4 5 0 3 \n",
"5 6 0 3 \n",
"6 7 0 1 \n",
"7 8 0 3 \n",
"8 9 1 3 \n",
"9 10 1 2 \n",
"\n",
" Name Sex Age SibSp \\\n",
"0 Braund, Mr. Owen Harris male 22.0 1 \n",
"1 Cumings, Mrs. John Bradley (Florence Briggs Th... female 38.0 1 \n",
"2 Heikkinen, Miss. Laina female 26.0 0 \n",
"3 Futrelle, Mrs. Jacques Heath (Lily May Peel) female 35.0 1 \n",
"4 Allen, Mr. William Henry male 35.0 0 \n",
"5 Moran, Mr. James male NaN 0 \n",
"6 McCarthy, Mr. Timothy J male 54.0 0 \n",
"7 Palsson, Master. Gosta Leonard male 2.0 3 \n",
"8 Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg) female 27.0 0 \n",
"9 Nasser, Mrs. Nicholas (Adele Achem) female 14.0 1 \n",
"\n",
" Parch Ticket Fare Cabin Embarked \n",
"0 0 A/5 21171 7.2500 NaN S \n",
"1 0 PC 17599 71.2833 C85 C \n",
"2 0 STON/O2. 3101282 7.9250 NaN S \n",
"3 0 113803 53.1000 C123 S \n",
"4 0 373450 8.0500 NaN S \n",
"5 0 330877 8.4583 NaN Q \n",
"6 0 17463 51.8625 E46 S \n",
"7 1 349909 21.0750 NaN S \n",
"8 2 347742 11.1333 NaN S \n",
"9 0 237736 30.0708 NaN C "
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Let's print some observations to see the data\n",
"train_data.head(10)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"_cell_guid": "304f36e8-656f-a29e-3af6-5b8a2e5eeedf",
"_uuid": "743833e71c8e759db8d1e5decafd12311483b3ee"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['PassengerId', 'Survived', 'Pclass', 'Name', 'Sex', 'Age', 'SibSp', 'Parch', 'Ticket', 'Fare', 'Cabin', 'Embarked']\n",
" PassengerId Survived Pclass Age SibSp \\\n",
"count 891.000000 891.000000 891.000000 714.000000 891.000000 \n",
"mean 446.000000 0.383838 2.308642 29.699118 0.523008 \n",
"std 257.353842 0.486592 0.836071 14.526497 1.102743 \n",
"min 1.000000 0.000000 1.000000 0.420000 0.000000 \n",
"25% 223.500000 0.000000 2.000000 20.125000 0.000000 \n",
"50% 446.000000 0.000000 3.000000 28.000000 0.000000 \n",
"75% 668.500000 1.000000 3.000000 38.000000 1.000000 \n",
"max 891.000000 1.000000 3.000000 80.000000 8.000000 \n",
"\n",
" Parch Fare \n",
"count 891.000000 891.000000 \n",
"mean 0.381594 32.204208 \n",
"std 0.806057 49.693429 \n",
"min 0.000000 0.000000 \n",
"25% 0.000000 7.910400 \n",
"50% 0.000000 14.454200 \n",
"75% 0.000000 31.000000 \n",
"max 6.000000 512.329200 \n"
]
}
],
"source": [
"# print list of variables\n",
"print(list(train_data))\n",
"\n",
"# print statistics\n",
"print(train_data.describe())\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
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]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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Yy86g4p3bPUhCjIW3bvUW5jIhBFkacnd3QjuNyGbjljYu4fOwi+LORvvChGalH+2VtPb7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\nE7wTe8LhtEQISTMOKAqN0Qa826EAuI1sdCO0shRVxUavXhhfhLbuHzU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rfOUrXwHgO9/5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6XVDqvF97/35K63qcbe+vIL87xzfcDf/vB9B2bJnG1Z/PXLC5Q8hycfMEuUx2WmVRR6dV3B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1CyhjkOXj9zDqJiUMzPCcchZEgUAvteeZlTHXFQcu+qmcyG2dRpfnIwSeQFJIcMbx1JXG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mniOpBmFUtztzYM/KFjXRzHIUlLHjze2aMI5bBoqcJI9pk3PjBLGLoMRyUPHu3iuuB5rm78yJ6b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MyXKJEEzt2cN2QG9UVOQ97Bp8gPnJ4iDPJbkojmGbinSyKfMcE9cu0aq61MoOQkwazybH3OyF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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fe8513f0278>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Let's do some plotting\n",
"from pandas.plotting import scatter_matrix\n",
"\n",
"scatter_matrix(train_data, alpha=0.2, figsize=(20, 20), diagonal='kde')"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7fe8513f0748>"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAd8AAAFKCAYAAABcq1WoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fe84cce3f60>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"train_data.Age.hist(bins = 40)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"PassengerId int64\n",
"Survived int64\n",
"Pclass int64\n",
"Name object\n",
"Sex int64\n",
"Age float64\n",
"SibSp int64\n",
"Parch int64\n",
"Ticket object\n",
"Fare float64\n",
"Cabin object\n",
"Embarked float64\n",
"dtype: object"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Need to code the gender of the passenger as numeric\n",
"train_data.Sex.dtypes\n",
"\n",
"def gender(x):\n",
" if x == \"Male\":\n",
" return 1\n",
" else:\n",
" return 0\n",
"\n",
"\n",
"train_data[\"Sex\"] = train_data[\"Sex\"].apply(gender)\n",
"train_data.Sex.dtypes\n",
"\n",
"# Need to code the port of embarkation as C = 0, Q = 1, S = 2\n",
"def embarkation(x):\n",
" switcher = {\n",
" \"C\": 0,\n",
" \"Q\": 1,\n",
" \"S\": 2,\n",
" }\n",
" return switcher.get(x)\n",
"\n",
"train_data[\"Embarked\"] = train_data[\"Embarked\"].apply(embarkation)\n",
"train_data.Embarked.dtypes\n",
"train_data.Embarked.head(10)\n",
"\n",
"train_data.dtypes\n"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" Pclass Sex Age SibSp Parch Fare \\\n",
"count 712.000000 712.0 712.000000 712.000000 712.000000 712.000000 \n",
"mean 2.240169 0.0 29.642093 0.514045 0.432584 34.567251 \n",
"std 0.836854 0.0 14.492933 0.930692 0.854181 52.938648 \n",
"min 1.000000 0.0 0.420000 0.000000 0.000000 0.000000 \n",
"25% 1.000000 0.0 20.000000 0.000000 0.000000 8.050000 \n",
"50% 2.000000 0.0 28.000000 0.000000 0.000000 15.645850 \n",
"75% 3.000000 0.0 38.000000 1.000000 1.000000 33.000000 \n",
"max 3.000000 0.0 80.000000 5.000000 6.000000 512.329200 \n",
"\n",
" Embarked Survived \n",
"count 712.000000 712.000000 \n",
"mean 1.595506 0.404494 \n",
"std 0.779038 0.491139 \n",
"min 0.000000 0.000000 \n",
"25% 2.000000 0.000000 \n",
"50% 2.000000 0.000000 \n",
"75% 2.000000 1.000000 \n",
"max 2.000000 1.000000 \n"
]
}
],
"source": [
"# Train model\n",
" # Select the features used. Starts with almost all of them \n",
" # (excluding tip amount of course)\n",
"features = ['Pclass', \n",
" 'Sex', \n",
" 'Age', \n",
" 'SibSp', \n",
" 'Parch', \n",
" 'Fare', \n",
" 'Embarked',\n",
" 'Survived']\n",
"\n",
"target = 'Survived'\n",
"\n",
"# Drop any of the row that contains a NaN\n",
"df = train_data[features].dropna(axis=0, how='any')\n",
"\n",
"df.dtypes\n",
"print(df[features].describe())"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Benchmarking RFC:\n",
"The out of bag score is: 0.6910.\n"
]
},
{
"data": {
"text/plain": [
"0.976123595505618"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"\n",
" # Create first a non-optimized random forest regressor using the aforementioned features\n",
" # This will serve as a baseline for benchmarking \n",
" # We will get a feel on the important features and decide which ones to keep\n",
"features = ['Pclass', \n",
" 'Sex', \n",
" 'Age', \n",
" 'SibSp', \n",
" 'Parch', \n",
" 'Fare', \n",
" 'Embarked'] \n",
"rfc = RandomForestClassifier(n_estimators=50,\n",
" oob_score=True,\n",
" max_features=None,\n",
" n_jobs=-1)\n",
" \n",
" # Train the random forest\n",
"rfc.fit(df[features], df[target])\n",
"\n",
"print(\"\\nBenchmarking RFC:\")\n",
" \n",
"# Print the oob score, which is the R2 based on oob_predictions\n",
"print(\"The out of bag score is: %.4f.\" %(rfc.oob_score_))\n",
"\n",
"y_pred = rfc.predict(df[features])\n",
"\n",
"rfc.score(df[features], df[target])\n"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.976123595505618"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sum(y_pred == df[target]).sum()/len(y_pred)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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0QZ8+fRAaGopJkybley45OVnrhekKT1gjMl6HDu3HtGmT8cEHwzBzZiBkMhk+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\nRK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fe84c070ef0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fpr_rt_lm, tpr_rt_lm, _ = roc_curve(df[target], y_pred)\n",
"\n",
"plt.figure(1)\n",
"plt.plot([0, 1], [0, 1], 'k--')\n",
"plt.plot(fpr_rt_lm, tpr_rt_lm, label='RT')\n",
"plt.xlabel('False positive rate')\n",
"plt.ylabel('True positive rate')\n",
"plt.title('ROC curve')\n",
"plt.legend(loc='best')\n",
"plt.show()\n"
]
}
],
"metadata": {
"_change_revision": 1,
"_is_fork": false,
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.1"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
| 0001/479/1479756.ipynb | s3://data-agents/kaggle-outputs/sharded/034_00001.jsonl.gz |
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 0 ns, sys: 0 ns, total: 0 ns\n",
"Wall time: 5.72 µs\n"
]
}
],
"source": [
"%time\n",
"import numpy as np\n",
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 0 ns, sys: 0 ns, total: 0 ns\n",
"Wall time: 5.01 µs\n"
]
}
],
"source": [
"%time\n",
"df_train = pd.read_csv('../input/train.csv')\n",
"np_train_x = np.reshape(df_train.values[:, 1:].astype(np.uint8), (df_train.shape[0], 28, 28))\n",
"np_train_y = np.reshape(df_train.values[:, 0].astype(np.uint8), (df_train.shape[0], 1))\n",
"df_test = pd.read_csv('../input/test.csv')\n",
"np_test_x = np.reshape(df_test.values.astype(np.uint8), (df_test.shape[0], 28, 28))"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 0 ns, sys: 0 ns, total: 0 ns\n",
"Wall time: 6.91 µs\n"
]
}
],
"source": [
"%time\n",
"np.save('./np_train_x.npy', np_train_x)\n",
"np.save('./np_train_y.npy', np_train_y)\n",
"np.save('./np_test_x.npy', np_test_x)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1 loop, best of 3: 7.27 s per loop\n"
]
}
],
"source": [
"%%timeit\n",
"df_train = pd.read_csv('../input/train.csv')\n",
"np_train_x = np.reshape(df_train.values[:, 1:].astype(np.uint8), (df_train.shape[0], 28, 28))\n",
"np_train_y = np.reshape(df_train.values[:, 0].astype(np.uint8), (df_train.shape[0], 1))\n",
"df_test = pd.read_csv('../input/test.csv')\n",
"np_test_x = np.reshape(df_test.values.astype(np.uint8), (df_test.shape[0], 28, 28))"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"100 loops, best of 3: 18.4 ms per loop\n"
]
}
],
"source": [
"%%timeit\n",
"np_train_x = np.load('./np_train_x.npy')\n",
"np_train_y = np.load('./np_train_y.npy')\n",
"np_test_x = np.load('./np_train_x.npy')"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.1"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
| 0001/479/1479769.ipynb | s3://data-agents/kaggle-outputs/sharded/034_00001.jsonl.gz |
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"_cell_guid": "4359736b-aa6d-ec34-6574-278de46b17dc",
"_uuid": "b0f1fdcb52d8298cc41c901faaa793e57c498fd5",
"collapsed": true
},
"outputs": [],
"source": [
"import gpxpy\n",
"import pandas as pd\n",
"import numpy as np\n",
"import math\n",
"import matplotlib.pyplot as plt\n",
"pd.set_option('display.max_rows',50)\n",
"import os \n",
"import re\n",
"import time\n",
"%matplotlib inline"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "15ed36e1-d7f9-c245-9415-6e89e2652488",
"_uuid": "6bf95a3a7435b7ee4ce614a8abee3943d1702311"
},
"source": [
"### Calculate Angle from Lat-Lon"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"_cell_guid": "cf23c18e-5f5b-bf96-f15c-ff5ee73e3fb5",
"_uuid": "a7a3347d72e06af2f8545661b3f7af824d9dda6c",
"collapsed": true
},
"outputs": [],
"source": [
"#May want to replace with geopy\n",
"def calculate_bearing(pointA, pointB):\n",
"\n",
" if (type(pointA) != tuple) or (type(pointB) != tuple):\n",
" raise TypeError(\"Only tuples are supported as arguments\")\n",
"\n",
" lat1 = math.radians(pointA[0])\n",
" lat2 = math.radians(pointB[0]) \n",
" diffLong = math.radians(pointB[1] - pointA[1])\n",
"\n",
" x = math.sin(diffLong) * math.cos(lat2)\n",
" y = math.cos(lat1) * math.sin(lat2) - (math.sin(lat1)\n",
" * math.cos(lat2) * math.cos(diffLong))\n",
"\n",
" bearing = np.rad2deg(np.arctan2(x, y))\n",
" compass_bearing = bearing % 360;\n",
" \n",
" \n",
" return compass_bearing"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "e2df8136-3506-1e06-9b44-b2f647d45927",
"_uuid": "84126d89bb927d9fe563aa3685db8f0dd9731b49"
},
"source": [
"### Read into dataframe"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"_cell_guid": "b3ab18e3-992a-2dba-d4b2-4cc9fd5a3d6d",
"_uuid": "0dff3702bbfd63dc0a71521c1a342c49c458006f",
"collapsed": true
},
"outputs": [],
"source": [
"def add_angle_difference(df_session,Angle_Difference,Wind_Direction):\n",
" df_session[Angle_Difference] = np.nan\n",
" df_session[Angle_Difference] = 180 - abs(abs(df_session[Wind_Direction] - df_session['Bearing']) - 180) \n",
" \n",
" return df_session"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"_cell_guid": "34df0b73-97b9-5dca-964b-0c2f823b5998",
"_uuid": "df21c1f851942a3b5c0a715e3c4a8c88f3a4b34e",
"collapsed": true
},
"outputs": [],
"source": [
"def filter_by_speed(df_session,lower_bound,upper_bound):\n",
" df_session = df_session[(df_session['Knots'] > lower_bound) & (df_session['Knots'] < upper_bound)]\n",
" return df_session"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"_cell_guid": "bb185519-23c5-8630-15ff-e7d81a4052e8",
"_uuid": "9be36c683eee2f341dcf762cc649b45e8407ff37",
"collapsed": true
},
"outputs": [],
"source": [
"def find_upwind_tack_angles(df_session):\n",
" \n",
" list_tack_angles = [None] * 4\n",
" angle_bounds = [[None,None]] * 4\n",
" not_string = \"\"\n",
" buffer_around_mode_bearing = 30 #to make sure we don't classify the same tack twice\n",
" \n",
" #find the tack angle\n",
" for i in range(0,4):\n",
" if i == 0:\n",
" list_tack_angles[i] = df_session['Bearing_Rounded'].mode()[0] \n",
" else:\n",
" if i > 1:\n",
" not_string += \" | \" \n",
" if angle_bounds[i-1][0] < angle_bounds[i-1][1]: #so between 60 and 120 is an example\n",
" not_string += \"(df_session['Bearing_Rounded'].between(%d,%d))\" % (angle_bounds[i-1][0],angle_bounds[i-1][1])\n",
" else: #so between 345 and 45 is an example\n",
" not_string += \"(df_session['Bearing_Rounded'] > %d) | (df_session['Bearing_Rounded'] < %d)\" % (angle_bounds[i-1][0],angle_bounds[i-1][1]) \n",
" \n",
" not_string_exec = \"list_tack_angles[%d] = df_session[~(%s)]['Bearing_Rounded'].mode()[0]\" % (i,not_string) \n",
" exec(not_string_exec) \n",
" angle_bounds[i] = [((list_tack_angles[i]-buffer_around_mode_bearing)%360),((list_tack_angles[i]+buffer_around_mode_bearing)%360)]\n",
" speed_dict = dict()\n",
" \n",
" for tack_angle in list_tack_angles:\n",
" speed_dict[tack_angle] = df_session[df_session['Bearing_Rounded'] == tack_angle]['Knots'].mean()\n",
"\n",
" list_tack_angles = sorted(speed_dict, key=speed_dict.get)\n",
" \n",
" \n",
" direction_tack = dict()\n",
" if ((list_tack_angles[0]-list_tack_angles[1]) % 360) < ((list_tack_angles[1]-list_tack_angles[0]) % 360):\n",
" \n",
" direction_tack['upwind_port'] = list_tack_angles[0]\n",
" direction_tack['upwind_starboard'] = list_tack_angles[1]\n",
" else:\n",
" direction_tack['upwind_port'] = list_tack_angles[1]\n",
" direction_tack['upwind_starboard'] = list_tack_angles[0]\n",
" \n",
" return direction_tack"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"_cell_guid": "7aa16c41-f55d-0836-bb48-ef3789002dc8",
"_uuid": "30e72b0602338d7333faef198bc53f54fccd1af1",
"collapsed": true
},
"outputs": [],
"source": [
"def add_wind_direction(df_session):\n",
" \n",
" direction_tack = find_upwind_tack_angles(df_session)\n",
" \n",
" approx_wind_direction_calc_from_upwind = (direction_tack['upwind_port'] - (((direction_tack['upwind_port'] - direction_tack['upwind_starboard']) % 360)/2))%360\n",
" \n",
" df_session['Wind_Direction'] = approx_wind_direction_calc_from_upwind\n",
" return df_session\n",
"\n",
" #approx_wind_direction_calc_from_downwind = direction_tack['downwind_port'] - ((direction_tack['downwind_port'] - direction_tack['downwind_starboard'])%360/2)\n",
"\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"_cell_guid": "f589d98d-92cd-3cd8-f9a6-d0eb7e5b8119",
"_uuid": "25507d7024f5f5e6ba30fca9591b53bf51ed3c2e",
"collapsed": true
},
"outputs": [],
"source": [
"def add_VMG(df_session,Angle_Difference,VMG):\n",
" df_session[VMG] = df_session['Knots'] * np.cos(np.radians((df_session[Angle_Difference])))\n",
" return df_session"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"_cell_guid": "d08400e2-ccd6-5bb7-e781-8080ad4e274f",
"_uuid": "cfa8ef7a566e368fd67ffd0a33b5e57a3f1ba8b0",
"collapsed": true
},
"outputs": [],
"source": [
"def add_tack(df_session):\n",
" df_session['tack'] = ''\n",
" df_session.loc[((df_session['Bearing'] + df_session['Angle_Difference']) % 360) == df_session['Wind_Direction'],'tack'] = 'Starboard'\n",
" df_session.loc[df_session['tack'] == '','tack'] = 'Port'\n",
" return df_session"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" ### Allowing Wind to Swing Around "
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"def infer_wind_direction(df_session):\n",
" upwind_anglediff_mean = df_session[(df_session['Direction'] == 'Upwind') & (df_session['Pushing'] == True)][['Angle_Difference']].mean()\n",
" #commented out downwind because downwind angles are less reliable\n",
" #downwind_anglediff_mean = df_session[(df_session['Direction'] == 'Downwind') & (df_session['Pushing'] == True)][['Angle_Difference']].mean()\n",
" df_session.loc[(df_session['Direction'] == 'Upwind') & (df_session['Pushing'] == True),'Wind_Direction_Inferred'] = df_session[(df_session['Direction'] == 'Upwind') & (df_session['Pushing'] == True)]['Angle_Difference'] + df_session[(df_session['Direction'] == 'Upwind') & (df_session['Pushing'] == True)]['Wind_Direction'] - float(upwind_anglediff_mean) \n",
"\n",
" df_session['Wind_Direction_Inferred_Smooth'] = np.nan\n",
" df_session.loc[df_session['Wind_Direction_Inferred'].notnull(),'Wind_Direction_Inferred_Smooth'] = df_session[df_session['Wind_Direction_Inferred'].notnull()]['Wind_Direction_Inferred'].rolling(window=100,center=True).mean()\n",
" df_session['Wind_Direction_Inferred_Smooth'] = df_session['Wind_Direction_Inferred_Smooth'].fillna(method='pad')\n",
" \n",
" df_session = add_angle_difference(df_session,'Angle_Difference_Inferred','Wind_Direction_Inferred_Smooth')\n",
" df_session = add_VMG(df_session,'Angle_Difference_Inferred','VMG_Inferred')\n",
" return df_session"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"_cell_guid": "d514ed1a-58dd-9421-15d9-aedffc4d28cf",
"_uuid": "9ce52694cb100595f670e7319044bc8776f41466"
},
"outputs": [],
"source": [
"def create_dataframe(gpx_file,time=None):\n",
" gpx = gpxpy.parse(open(gpx_file))\n",
" track = gpx.tracks[0]\n",
" segment = track.segments[0]\n",
" \n",
" data = []\n",
" segment_length = segment.length_3d()\n",
" for point_idx, point in enumerate(segment.points):\n",
" data.append([point.longitude, point.latitude,\n",
" point.time, segment.get_speed(point_idx)])\n",
"\n",
" columns = ['Longitude', 'Latitude', 'Time', 'Speed']\n",
" df_session = pd.DataFrame(data, columns=columns)\n",
" \n",
" df_session['Bearing'] = np.nan\n",
" for i in range(1,len(df_session)): \n",
" df_session.iloc[i,df_session.columns.get_loc('Bearing')] = calculate_bearing((df_session['Latitude'][i-1], df_session['Longitude'][i-1]),(df_session['Latitude'][i], df_session['Longitude'][i]))\n",
" \n",
" #round the bearning to the nearest \"base\" degrees\n",
" base = 3 #if base = 5, then round to the nearest five degrees\n",
" df_session['Bearing_Rounded'] = np.round(base * np.round(df_session['Bearing']/base),0)\n",
" \n",
" if time == None:\n",
" df_session.index = df_session['Time']\n",
" df_session['Knots'] = df_session['Speed']*1.94384\n",
" \n",
" df_session = filter_by_speed(df_session,14,30)\n",
" if (len(df_session) < 500): #not enough observations \n",
" return False\n",
" \n",
" del(df_session['Time'])\n",
" del(df_session['Speed'])\n",
" \n",
" df_session = add_wind_direction(df_session)\n",
" df_session = add_angle_difference(df_session,'Angle_Difference','Wind_Direction') \n",
" df_session = add_VMG(df_session,'Angle_Difference','VMG')\n",
" df_session = add_tack(df_session)\n",
" \n",
" #Defined pushing as the 40th percentile. Assumes that I'm pushing for 60% of the sessions\n",
" UPWIND_LOWER_ANGLEDIFF = 35\n",
" UPWIND_UPPER_ANGLEDIFF = 65\n",
" DOWNWIND_LOWER_ANGLEDIFF = 130\n",
"\n",
" df_session['Direction'] = None\n",
" df_session.loc[(df_session['Angle_Difference'] < UPWIND_UPPER_ANGLEDIFF) & (df_session['Angle_Difference'] > UPWIND_LOWER_ANGLEDIFF),'Direction'] = 'Upwind'\n",
" df_session.loc[df_session['Angle_Difference'] > DOWNWIND_LOWER_ANGLEDIFF,'Direction'] = 'Downwind'\n",
"\n",
" pushing_upwind = df_session[df_session['Direction'] == 'Upwind']['Knots'].quantile(q=.4)\n",
" pushing_downwind = df_session[df_session['Direction'] == 'Downwind']['Knots'].quantile(q=.4)\n",
"\n",
" df_session['Pushing'] = False\n",
" df_session.loc[(df_session['Direction'] == 'Upwind') & (df_session['Knots'] > pushing_upwind) & (df_session['Knots'] < 26),'Pushing'] = True\n",
" df_session.loc[(df_session['Direction'] == 'Downwind') & (df_session['Knots'] > pushing_downwind) & (df_session['Knots'] < 32),'Pushing'] = True\n",
" \n",
" df_session = infer_wind_direction(df_session)\n",
" \n",
" return df_session"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"_cell_guid": "5543ced0-16de-89f8-c396-dc68087a864d",
"_uuid": "85771022cc2b602e163da6e9e77f7f286af51778"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" Upwind_VMG_Mean Upwind_Knots Upwind_Angle_Difference\n",
"20170519-012600-Ride.gpx NaN 22.3032 NaN\n",
" Upwind_VMG_Mean Upwind_Knots Upwind_Angle_Difference\n",
"20170520-001002-Ride.gpx 12.6336 18.8649 47.5269\n",
" Upwind_VMG_Mean Upwind_Knots Upwind_Angle_Difference\n",
"20170521-223157-Ride.gpx 11.7576 18.8934 51.116\n",
" Upwind_VMG_Mean Upwind_Knots Upwind_Angle_Difference\n",
"20170603-001123-Ride.gpx 10.5335 18.2557 54.4433\n"
]
}
],
"source": [
"directory = \"../input/gps-watch-data/anthony_activities/\"\n",
"\n",
"to_analyze = os.listdir(directory)[-5:] #just does the last 5s\n",
"\n",
"df_session_summaries = pd.DataFrame(columns=['Upwind_VMG_Mean','Upwind_Knots','Upwind_Angle_Difference','Upwind_VMG_075','Downwind_VMG_Mean','Downwind_Knots','Downwind_Angle_Difference','Downwind_Knots_075','Upwind_VMG_Starboard','Upwind_Knots_Starboard','Upwind_Angle_Starboard','Upwind_VMG_Port','Upwind_Knots_Port','Upwind_Angle_Port','Downwind_VMG_Starboard','Downwind_Knots_Starboard','Downwind_Angle_Starboard','Downwind_VMG_Port','Downwind_Knots_Port','Downwind_Angle_Port'],index=to_analyze)\n",
"\n",
"for gpx_file in to_analyze:\n",
" if (os.stat(directory + gpx_file).st_size > 50000):\n",
" df_session = create_dataframe(directory + gpx_file)\n",
" if (not isinstance(df_session, int)): \n",
" \n",
" df_session = df_session[df_session['Pushing'] == True]\n",
" \n",
" VMG = 'VMG_Inferred'\n",
" Angle_Difference = 'Angle_Difference_Inferred'\n",
" \n",
" summary_list = df_session[(df_session['Direction'] == 'Upwind')][[VMG,'Knots',Angle_Difference]].mean().tolist()\n",
" summary_list = summary_list + df_session[(df_session['Direction'] == 'Upwind')][[VMG]].quantile(q=0.75).tolist()\n",
" summary_list = summary_list + df_session[(df_session['Direction'] == 'Downwind')][[VMG,'Knots',Angle_Difference]].mean().tolist()\n",
" summary_list = summary_list + df_session[(df_session['Direction'] == 'Downwind')][['Knots']].quantile(q=0.75).tolist()\n",
" summary_list = summary_list + df_session[(df_session['Direction'] == 'Upwind') & (df_session['tack'] == 'Starboard')][[VMG,'Knots',Angle_Difference]].mean().tolist()\n",
" summary_list = summary_list + df_session[(df_session['Direction'] == 'Upwind') & (df_session['tack'] == 'Port')][[VMG,'Knots',Angle_Difference]].mean().tolist()\n",
" summary_list = summary_list + df_session[(df_session['Direction'] == 'Downwind') & (df_session['tack'] == 'Starboard')][[VMG,'Knots',Angle_Difference]].mean().tolist()\n",
" summary_list = summary_list + df_session[(df_session['Direction'] == 'Downwind') & (df_session['tack'] == 'Port')][[VMG,'Knots',Angle_Difference]].mean().tolist()\n",
" \n",
" df_session_summaries.loc[df_session_summaries.index == gpx_file,['Upwind_VMG_Mean','Upwind_Knots','Upwind_Angle_Difference','Upwind_VMG_075','Downwind_VMG_Mean','Downwind_Knots','Downwind_Angle_Difference','Downwind_Knots_075','Upwind_VMG_Starboard','Upwind_Knots_Starboard','Upwind_Angle_Starboard','Upwind_VMG_Port','Upwind_Knots_Port','Upwind_Angle_Port','Downwind_VMG_Starboard','Downwind_Knots_Starboard','Downwind_Angle_Starboard','Downwind_VMG_Port','Downwind_Knots_Port','Downwind_Angle_Port']] = summary_list \n",
" \n",
" print(df_session_summaries[df_session_summaries.index == gpx_file][['Upwind_VMG_Mean','Upwind_Knots','Upwind_Angle_Difference']])\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"_cell_guid": "8ef7343c-0577-4e0a-92f9-688fa129016d",
"_uuid": "e493658ee5898322318bd24af16c2ef2504585db"
},
"outputs": [],
"source": [
"df_session_summaries.index = df_session_summaries.index.str[0:15] \n",
"df_session_summaries.index = pd.to_datetime(df_session_summaries.index,format=\"%Y%m%d-%H%M%S\")\n",
"\n",
"df_session_summaries.to_csv('df_session_summary_' + time.strftime(\"%Y%m%d\") + '.csv')"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
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" text-align: left;\n",
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"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Upwind_VMG_Mean</th>\n",
" <th>Upwind_Knots</th>\n",
" <th>Upwind_Angle_Difference</th>\n",
" <th>Upwind_VMG_075</th>\n",
" <th>Downwind_VMG_Mean</th>\n",
" <th>Downwind_Knots</th>\n",
" <th>Downwind_Angle_Difference</th>\n",
" <th>Downwind_Knots_075</th>\n",
" <th>Upwind_VMG_Starboard</th>\n",
" <th>Upwind_Knots_Starboard</th>\n",
" <th>Upwind_Angle_Starboard</th>\n",
" <th>Upwind_VMG_Port</th>\n",
" <th>Upwind_Knots_Port</th>\n",
" <th>Upwind_Angle_Port</th>\n",
" <th>Downwind_VMG_Starboard</th>\n",
" <th>Downwind_Knots_Starboard</th>\n",
" <th>Downwind_Angle_Starboard</th>\n",
" <th>Downwind_VMG_Port</th>\n",
" <th>Downwind_Knots_Port</th>\n",
" <th>Downwind_Angle_Port</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2017-05-19 01:26:00</th>\n",
" <td>NaN</td>\n",
" <td>22.3032</td>\n",
" <td>NaN</td>\n",
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" <td>NaN</td>\n",
" <td>22.3032</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>20.9928</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>18.9869</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-05-20 00:10:02</th>\n",
" <td>12.6336</td>\n",
" <td>18.8649</td>\n",
" <td>47.5269</td>\n",
" <td>14.2893</td>\n",
" <td>-23.0881</td>\n",
" <td>24.0478</td>\n",
" <td>166.767</td>\n",
" <td>24.5538</td>\n",
" <td>9.50354</td>\n",
" <td>18.295</td>\n",
" <td>58.6095</td>\n",
" <td>13.2757</td>\n",
" <td>18.9756</td>\n",
" <td>45.2536</td>\n",
" <td>-23.0852</td>\n",
" <td>24.0512</td>\n",
" <td>166.667</td>\n",
" <td>-23.4648</td>\n",
" <td>23.465</td>\n",
" <td>179.805</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-05-21 22:31:57</th>\n",
" <td>11.7576</td>\n",
" <td>18.8934</td>\n",
" <td>51.116</td>\n",
" <td>13.2995</td>\n",
" <td>-20.5352</td>\n",
" <td>24.3411</td>\n",
" <td>148.209</td>\n",
" <td>24.9872</td>\n",
" <td>11.9577</td>\n",
" <td>19.1078</td>\n",
" <td>50.8073</td>\n",
" <td>11.5873</td>\n",
" <td>18.6938</td>\n",
" <td>51.3787</td>\n",
" <td>-19.7167</td>\n",
" <td>24.1952</td>\n",
" <td>145.127</td>\n",
" <td>-22.3743</td>\n",
" <td>24.7072</td>\n",
" <td>155.132</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-05-22 01:15:45</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <tr>\n",
" <th>2017-06-03 00:11:23</th>\n",
" <td>10.5335</td>\n",
" <td>18.2557</td>\n",
" <td>54.4433</td>\n",
" <td>11.755</td>\n",
" <td>-20.7229</td>\n",
" <td>23.9256</td>\n",
" <td>150.984</td>\n",
" <td>24.3359</td>\n",
" <td>10.6291</td>\n",
" <td>18.1243</td>\n",
" <td>53.7061</td>\n",
" <td>10.4708</td>\n",
" <td>18.3386</td>\n",
" <td>54.9269</td>\n",
" <td>-20.6707</td>\n",
" <td>23.8083</td>\n",
" <td>151.138</td>\n",
" <td>-21.1693</td>\n",
" <td>25.243</td>\n",
" <td>149.667</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Upwind_VMG_Mean Upwind_Knots Upwind_Angle_Difference \\\n",
"2017-05-19 01:26:00 NaN 22.3032 NaN \n",
"2017-05-20 00:10:02 12.6336 18.8649 47.5269 \n",
"2017-05-21 22:31:57 11.7576 18.8934 51.116 \n",
"2017-05-22 01:15:45 NaN NaN NaN \n",
"2017-06-03 00:11:23 10.5335 18.2557 54.4433 \n",
"\n",
" Upwind_VMG_075 Downwind_VMG_Mean Downwind_Knots \\\n",
"2017-05-19 01:26:00 NaN NaN 19.7478 \n",
"2017-05-20 00:10:02 14.2893 -23.0881 24.0478 \n",
"2017-05-21 22:31:57 13.2995 -20.5352 24.3411 \n",
"2017-05-22 01:15:45 NaN NaN NaN \n",
"2017-06-03 00:11:23 11.755 -20.7229 23.9256 \n",
"\n",
" Downwind_Angle_Difference Downwind_Knots_075 \\\n",
"2017-05-19 01:26:00 NaN 20.7358 \n",
"2017-05-20 00:10:02 166.767 24.5538 \n",
"2017-05-21 22:31:57 148.209 24.9872 \n",
"2017-05-22 01:15:45 NaN NaN \n",
"2017-06-03 00:11:23 150.984 24.3359 \n",
"\n",
" Upwind_VMG_Starboard Upwind_Knots_Starboard \\\n",
"2017-05-19 01:26:00 NaN 22.3032 \n",
"2017-05-20 00:10:02 9.50354 18.295 \n",
"2017-05-21 22:31:57 11.9577 19.1078 \n",
"2017-05-22 01:15:45 NaN NaN \n",
"2017-06-03 00:11:23 10.6291 18.1243 \n",
"\n",
" Upwind_Angle_Starboard Upwind_VMG_Port Upwind_Knots_Port \\\n",
"2017-05-19 01:26:00 NaN NaN NaN \n",
"2017-05-20 00:10:02 58.6095 13.2757 18.9756 \n",
"2017-05-21 22:31:57 50.8073 11.5873 18.6938 \n",
"2017-05-22 01:15:45 NaN NaN NaN \n",
"2017-06-03 00:11:23 53.7061 10.4708 18.3386 \n",
"\n",
" Upwind_Angle_Port Downwind_VMG_Starboard \\\n",
"2017-05-19 01:26:00 NaN NaN \n",
"2017-05-20 00:10:02 45.2536 -23.0852 \n",
"2017-05-21 22:31:57 51.3787 -19.7167 \n",
"2017-05-22 01:15:45 NaN NaN \n",
"2017-06-03 00:11:23 54.9269 -20.6707 \n",
"\n",
" Downwind_Knots_Starboard Downwind_Angle_Starboard \\\n",
"2017-05-19 01:26:00 20.9928 NaN \n",
"2017-05-20 00:10:02 24.0512 166.667 \n",
"2017-05-21 22:31:57 24.1952 145.127 \n",
"2017-05-22 01:15:45 NaN NaN \n",
"2017-06-03 00:11:23 23.8083 151.138 \n",
"\n",
" Downwind_VMG_Port Downwind_Knots_Port Downwind_Angle_Port \n",
"2017-05-19 01:26:00 NaN 18.9869 NaN \n",
"2017-05-20 00:10:02 -23.4648 23.465 179.805 \n",
"2017-05-21 22:31:57 -22.3743 24.7072 155.132 \n",
"2017-05-22 01:15:45 NaN NaN NaN \n",
"2017-06-03 00:11:23 -21.1693 25.243 149.667 "
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df_session_summaries"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "9312c089-6a11-4396-a318-3006cdc840de",
"_uuid": "e9a3b975cf1233a8313edca6434f2faa262dd623"
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| 0001/479/1479773.ipynb | s3://data-agents/kaggle-outputs/sharded/034_00001.jsonl.gz |
{
"cells": [
{
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"metadata": {
"_cell_guid": "cdf01fa8-a939-4e68-8149-885f76fdde47",
"_uuid": "e1e6cf1a0e121b17edbea84b99401f9ea3377a6d"
},
"source": [
"1. Introduction\n",
"1. \n",
"\n",
"1. sadasda\n",
"1. 1. 1. dsd\n",
"2w2das1. 1. 1.1 Using libraries\n",
" 1.2 Train & test data\n",
" 1.3 Data structure and content\n",
" 1.4 Changing data format\n",
"2 Data cleaning\n",
" 2.1 Too long trip_duraiton\n",
" 2.2 Too short trip_duration\n",
" 2.3 Wierd location \n",
" 2.4 Not moving\n",
"3 Expanded features\n",
" 3.1 Feature having relationship with airport\n",
" 3.2 \n",
"4 External features\n",
" 4.1. Hourly weather data\n",
" 4.2 Crime \n",
"3 Feature relations with trip_duration\n",
" 2.1 Pickup date/time vs trip_duration\n",
" 2.2 Passenger count and Vendor vs trip_duration\n",
" 2.3 Store and Forward vs trip_duration\n",
" 2.4 \n",
"4 Feature engineering\n",
" 4.1 Direct distance of the trip\n",
" 4.2 Travel speed\n",
" 4.3 Bearing direction\n",
" 4.4 Airport distance\n",
"5 Data cleaning\n",
" 5.1 Extreme trip durations\n",
" 5.1.1 Longer than a day\n",
" 5.1.2 Close to 24 hours\n",
" 5.1.3 Shorter than a few minutes\n",
" 5.2 Intermission - The best spurious trips\n",
" 5.3 Final cleaning\n",
"6 External data\n",
" 6.1 Weather reports\n",
" 6.1.1 Data import, overview, formatting, joining\n",
" 6.1.2 Visualisation and impact on trip_duration\n",
" 6.2 Fastest Routes\n",
" 6.2.1 Data import and overview\n",
" 6.2.2 New data visualisations\n",
" 6.2.3 Joining and derived features\n",
" 6.2.4 Visualisation and impact on trip_duration\n",
" 6.2.5 trip_duration vs total_travel_time - a look at curious delays\n",
"7 Correlations overview\n",
"8 An excursion into classification\n",
"9 A simple model and prediction\n",
" 9.1 Preparations\n",
" 9.1.1 Train vs test overlap\n",
" 9.1.2 Data formatting\n",
" 9.1.3 Feature selection, metric adjustment, validation split, and careful cleaning\n",
" 9.2 XGBoost parameters and fitting\n",
" 9.3 Feature importance\n",
" 9.4 Prediction and submission file\n",
" "
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "a9af0677-6450-4bca-ba99-d3d712419f87",
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"source": []
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{
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"_uuid": "2dc405dcb470b9c6d862a4a2a701d5c5749e5108"
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"source": [
"********"
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{
"cell_type": "code",
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"metadata": {
"_cell_guid": "c9b0f1eb-ba5b-427a-bc15-8c0e24af2de8",
"_uuid": "5580d837a3f94a01187b82933611c2ea17c9aaf2"
},
"outputs": [
{
"data": {
"text/html": [
"<ol class=list-inline>\n",
"\t<li>'sample_submission.csv'</li>\n",
"\t<li>'test.csv'</li>\n",
"\t<li>'train.csv'</li>\n",
"</ol>\n"
],
"text/latex": [
"\\begin{enumerate*}\n",
"\\item 'sample\\_submission.csv'\n",
"\\item 'test.csv'\n",
"\\item 'train.csv'\n",
"\\end{enumerate*}\n"
],
"text/markdown": [
"1. 'sample_submission.csv'\n",
"2. 'test.csv'\n",
"3. 'train.csv'\n",
"\n",
"\n"
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"[1] \"sample_submission.csv\" \"test.csv\" \"train.csv\" "
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},
"metadata": {},
"output_type": "display_data"
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],
"source": [
"# This R environment comes with all of CRAN preinstalled, as well as many other helpful packages\n",
"# The environment is defined by the kaggle/rstats docker image: https://github.com/kaggle/docker-rstats\n",
"# For example, here's several helpful packages to load in \n",
"\n",
"library(ggplot2) # Data visualization\n",
"library(readr) # CSV file I/O, e.g. the read_csv function\n",
"\n",
"# Input data files are available in the \"../input/\" directory.\n",
"# For example, running this (by clicking run or pressing Shift+Enter) will list the files in the input directory\n",
"\n",
"list.files(\"../input\")\n",
"\n",
"# Any results you write to the current directory are saved as output.\n",
"# any code here#"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "R",
"language": "R",
"name": "ir"
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| 0001/479/1479977.ipynb | s3://data-agents/kaggle-outputs/sharded/034_00001.jsonl.gz |
{
"cells": [
{
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"_uuid": "996994915ad55c102cf5bff9b6fdcad3d8783fba"
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"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Using TensorFlow backend.\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
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" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
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" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
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" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
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" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
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" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
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" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
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" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
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" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
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" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
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" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
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" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
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" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
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" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
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" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
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" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
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" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
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" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
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" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
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" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
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" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
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" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
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" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
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" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
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" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
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" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n",
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n"
]
}
],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"import gc\n",
"import matplotlib.pyplot as plt\n",
"\n",
"%matplotlib inline\n",
"\n",
"pd.options.display.max_columns = 999\n",
"\n",
"\n",
"import xgboost as xgb\n",
"from xgboost.sklearn import XGBClassifier\n",
"from sklearn import model_selection\n",
"\n",
"from sklearn_pandas import DataFrameMapper\n",
"from sklearn.preprocessing import LabelEncoder, Imputer, StandardScaler\n",
"from sklearn.neighbors import NearestNeighbors\n",
"\n",
"import operator, random, pickle\n",
"import math, keras, datetime, keras.backend as K, tensorflow as tf, matplotlib.pyplot as plt, operator, random, pickle, glob, os, functools, itertools\n",
"from numpy.random import normal\n",
"\n",
"from keras import initializers\n",
"from keras.models import Model, Sequential\n",
"from keras.layers import *\n",
"from keras.optimizers import Adam\n",
"from keras.regularizers import l2\n",
"from keras.utils.data_utils import get_file\n"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"_cell_guid": "6a9740c0-d15d-4f26-9295-34e7b6f09afd",
"_uuid": "4ef1740565085ea9431fea1f7ba6477eb0428dfa",
"collapsed": true
},
"outputs": [],
"source": [
"train = pd.read_csv(\"../input/train_2016_v2.csv\", parse_dates=[\"transactiondate\"])"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"_cell_guid": "0b799f7b-dc64-4d9f-8bca-810ee83d78d4",
"_uuid": "bfa73ea664932e67a092311af4ccaeb67c8d3565"
},
"outputs": [],
"source": [
"prop = pd.read_csv(\"../input/properties_2016.csv\", low_memory=False)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"_cell_guid": "975901cd-1674-4302-81cf-31be105551b0",
"_uuid": "8eee75cd1a12e6c8ecf8076caad8efe4714505b9",
"collapsed": true
},
"outputs": [],
"source": [
"sample = pd.read_csv(\"../input/sample_submission.csv\")"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"_cell_guid": "096ff597-02d1-41c6-89c8-fe0d76293646",
"_uuid": "e1d4150c32f64b2df0bdeca292eca14c96eed9e0",
"collapsed": true
},
"outputs": [],
"source": [
"xls = pd.ExcelFile('../input/zillow_data_dictionary.xlsx')\n",
"sheets = {sh:xls.parse(sh) for sh in xls.sheet_names}"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"_cell_guid": "5ef3d819-86d1-45d1-b9fe-18821354f7f7",
"_uuid": "ad04c00060d0ea0f606bf8ebb2ce0d6ad6b6f348"
},
"outputs": [
{
"ename": "KeyError",
"evalue": "'airconditioningtypeid'",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m 2392\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2393\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2394\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc (pandas/_libs/index.c:5239)\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc (pandas/_libs/index.c:5085)\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item (pandas/_libs/hashtable.c:20405)\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item (pandas/_libs/hashtable.c:20359)\u001b[0;34m()\u001b[0m\n",
"\u001b[0;31mKeyError\u001b[0m: 'airconditioningtypeid'",
"\nDuring handling of the above exception, another exception occurred:\n",
"\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-6-cd8072e5d04e>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mprop\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mprop\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmerge\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msheets\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'AirConditioningTypeID'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mon\u001b[0m \u001b[0;34m=\u001b[0m\u001b[0;34m'airconditioningtypeid'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mhow\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'left'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mprop\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mprop\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmerge\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msheets\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'HeatingOrSystemTypeID'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mon\u001b[0m \u001b[0;34m=\u001b[0m\u001b[0;34m'heatingorsystemtypeid'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mhow\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'left'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0mprop\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mprop\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmerge\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msheets\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'PropertyLandUseTypeID'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mon\u001b[0m \u001b[0;34m=\u001b[0m\u001b[0;34m'propertylandusetypeid'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mhow\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'left'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0mprop\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mprop\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmerge\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msheets\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'StoryTypeID'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mon\u001b[0m \u001b[0;34m=\u001b[0m\u001b[0;34m'storytypeid'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mhow\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'left'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mprop\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mprop\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmerge\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msheets\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'ArchitecturalStyleTypeID'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mon\u001b[0m \u001b[0;34m=\u001b[0m\u001b[0;34m'architecturalstyletypeid'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mhow\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'left'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36mmerge\u001b[0;34m(self, right, how, on, left_on, right_on, left_index, right_index, sort, suffixes, copy, indicator)\u001b[0m\n\u001b[1;32m 4818\u001b[0m \u001b[0mright_on\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mright_on\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mleft_index\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mleft_index\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4819\u001b[0m \u001b[0mright_index\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mright_index\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msort\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msort\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msuffixes\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msuffixes\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 4820\u001b[0;31m copy=copy, indicator=indicator)\n\u001b[0m\u001b[1;32m 4821\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4822\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mround\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdecimals\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/reshape/merge.py\u001b[0m in \u001b[0;36mmerge\u001b[0;34m(left, right, how, on, left_on, right_on, left_index, right_index, sort, suffixes, copy, indicator)\u001b[0m\n\u001b[1;32m 51\u001b[0m \u001b[0mright_on\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mright_on\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mleft_index\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mleft_index\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 52\u001b[0m \u001b[0mright_index\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mright_index\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msort\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msort\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msuffixes\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msuffixes\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 53\u001b[0;31m copy=copy, indicator=indicator)\n\u001b[0m\u001b[1;32m 54\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mop\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_result\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 55\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/reshape/merge.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, left, right, how, on, left_on, right_on, axis, left_index, right_index, sort, suffixes, copy, indicator)\u001b[0m\n\u001b[1;32m 556\u001b[0m (self.left_join_keys,\n\u001b[1;32m 557\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mright_join_keys\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 558\u001b[0;31m self.join_names) = self._get_merge_keys()\n\u001b[0m\u001b[1;32m 559\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 560\u001b[0m \u001b[0;31m# validate the merge keys dtypes. We may need to coerce\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/reshape/merge.py\u001b[0m in \u001b[0;36m_get_merge_keys\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 808\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mis_rkey\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrk\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 809\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mrk\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 810\u001b[0;31m \u001b[0mright_keys\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mright\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mrk\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_values\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 811\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 812\u001b[0m \u001b[0;31m# work-around for merge_asof(right_index=True)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 2060\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_multilevel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2061\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2062\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_column\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2063\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2064\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_getitem_column\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m_getitem_column\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 2067\u001b[0m \u001b[0;31m# get column\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2068\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_unique\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2069\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_item_cache\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2070\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2071\u001b[0m \u001b[0;31m# duplicate columns & possible reduce dimensionality\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36m_get_item_cache\u001b[0;34m(self, item)\u001b[0m\n\u001b[1;32m 1532\u001b[0m \u001b[0mres\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcache\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1533\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mres\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1534\u001b[0;31m \u001b[0mvalues\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_data\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1535\u001b[0m \u001b[0mres\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_box_item_values\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalues\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1536\u001b[0m \u001b[0mcache\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mres\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/internals.py\u001b[0m in \u001b[0;36mget\u001b[0;34m(self, item, fastpath)\u001b[0m\n\u001b[1;32m 3588\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3589\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0misnull\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3590\u001b[0;31m \u001b[0mloc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3591\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3592\u001b[0m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0misnull\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m 2393\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2394\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2395\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_maybe_cast_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2396\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2397\u001b[0m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtolerance\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtolerance\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc (pandas/_libs/index.c:5239)\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc (pandas/_libs/index.c:5085)\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item (pandas/_libs/hashtable.c:20405)\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item (pandas/_libs/hashtable.c:20359)\u001b[0;34m()\u001b[0m\n",
"\u001b[0;31mKeyError\u001b[0m: 'airconditioningtypeid'"
]
}
],
"source": [
"prop = prop.merge(sheets['AirConditioningTypeID'], on ='airconditioningtypeid', how='left')\n",
"prop = prop.merge(sheets['HeatingOrSystemTypeID'], on ='heatingorsystemtypeid', how='left')\n",
"prop = prop.merge(sheets['PropertyLandUseTypeID'], on ='propertylandusetypeid', how='left')\n",
"prop = prop.merge(sheets['StoryTypeID'], on ='storytypeid', how='left')\n",
"prop = prop.merge(sheets['ArchitecturalStyleTypeID'], on ='architecturalstyletypeid', how='left')\n",
"prop = prop.merge(sheets['TypeConstructionTypeID'], on ='typeconstructiontypeid', how='left')"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"_cell_guid": "361ad814-7423-45d6-817d-fdcf74270dbe",
"_uuid": "7a4b14668e293478f4ad05a33b1d19b21827bceb",
"collapsed": true
},
"outputs": [
{
"ename": "KeyError",
"evalue": "'airconditioningdesc'",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m 2392\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2393\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2394\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc (pandas/_libs/index.c:5239)\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc (pandas/_libs/index.c:5085)\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item (pandas/_libs/hashtable.c:20405)\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item (pandas/_libs/hashtable.c:20359)\u001b[0;34m()\u001b[0m\n",
"\u001b[0;31mKeyError\u001b[0m: 'airconditioningdesc'",
"\nDuring handling of the above exception, another exception occurred:\n",
"\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-7-804fba345235>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mprop\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'airconditioningdesc'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfillna\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Other'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minplace\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mprop\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'heatingorsystemdesc'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfillna\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Other'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minplace\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0mprop\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'propertylandusedesc'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfillna\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Other'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minplace\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0mprop\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'storydesc'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfillna\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Other'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minplace\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mprop\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'architecturalstyledesc'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfillna\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Other'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minplace\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 2060\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_multilevel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2061\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2062\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_column\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2063\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2064\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_getitem_column\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m_getitem_column\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 2067\u001b[0m \u001b[0;31m# get column\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2068\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_unique\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2069\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_item_cache\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2070\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2071\u001b[0m \u001b[0;31m# duplicate columns & possible reduce dimensionality\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36m_get_item_cache\u001b[0;34m(self, item)\u001b[0m\n\u001b[1;32m 1532\u001b[0m \u001b[0mres\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcache\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1533\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mres\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1534\u001b[0;31m \u001b[0mvalues\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_data\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1535\u001b[0m \u001b[0mres\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_box_item_values\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalues\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1536\u001b[0m \u001b[0mcache\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mres\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/internals.py\u001b[0m in \u001b[0;36mget\u001b[0;34m(self, item, fastpath)\u001b[0m\n\u001b[1;32m 3588\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3589\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0misnull\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3590\u001b[0;31m \u001b[0mloc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3591\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3592\u001b[0m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0misnull\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m 2393\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2394\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2395\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_maybe_cast_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2396\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2397\u001b[0m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtolerance\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtolerance\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc (pandas/_libs/index.c:5239)\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc (pandas/_libs/index.c:5085)\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item (pandas/_libs/hashtable.c:20405)\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item (pandas/_libs/hashtable.c:20359)\u001b[0;34m()\u001b[0m\n",
"\u001b[0;31mKeyError\u001b[0m: 'airconditioningdesc'"
]
}
],
"source": [
"prop['airconditioningdesc'].fillna('Other', inplace=True)\n",
"prop['heatingorsystemdesc'].fillna('Other', inplace=True)\n",
"prop['propertylandusedesc'].fillna('Other', inplace=True)\n",
"prop['storydesc'].fillna('Other', inplace=True)\n",
"prop['architecturalstyledesc'].fillna('Other', inplace=True)\n",
"prop['typeconstructiondesc'].fillna('Other', inplace=True)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"_cell_guid": "c5c27828-59f5-48f5-84c1-28c2a71101c1",
"_uuid": "d4097cdf3932546cfd9a8f47cf13dcd980ffbc8f"
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py:4: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" after removing the cwd from sys.path.\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n",
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:992: DeprecationWarning: \n",
".ix is deprecated. Please use\n",
".loc for label based indexing or\n",
".iloc for positional indexing\n",
"\n",
"See the documentation here:\n",
"http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate_ix\n",
" return getattr(section, self.name)[new_key]\n"
]
}
],
"source": [
"waste_col = []\n",
"\n",
"for col in prop.columns:\n",
" if prop.ix[:,col].isnull().sum()/prop.shape[0] >0.9:\n",
" waste_col.append(col)\n",
" else:\n",
" continue"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"_cell_guid": "df713c39-4e3e-43bb-82c0-e2dc46526125",
"_uuid": "ebec2eea1c67e1b5d5d8685066b39b6ef98f5fcb",
"collapsed": true
},
"outputs": [],
"source": [
"prop.drop(waste_col,axis=1,inplace=True)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"_cell_guid": "477d6437-fd69-4266-99a6-327850f1927e",
"_uuid": "b9a8671d3065f5cafc8717c9557e0e93ccbd8b49"
},
"outputs": [
{
"data": {
"text/html": [
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" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>parcelid</th>\n",
" <th>airconditioningtypeid</th>\n",
" <th>bathroomcnt</th>\n",
" <th>bedroomcnt</th>\n",
" <th>buildingqualitytypeid</th>\n",
" <th>calculatedbathnbr</th>\n",
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" <th>heatingorsystemtypeid</th>\n",
" <th>latitude</th>\n",
" <th>longitude</th>\n",
" <th>lotsizesquarefeet</th>\n",
" <th>poolcnt</th>\n",
" <th>pooltypeid7</th>\n",
" <th>propertycountylandusecode</th>\n",
" <th>propertylandusetypeid</th>\n",
" <th>propertyzoningdesc</th>\n",
" <th>rawcensustractandblock</th>\n",
" <th>regionidcity</th>\n",
" <th>regionidcounty</th>\n",
" <th>regionidneighborhood</th>\n",
" <th>regionidzip</th>\n",
" <th>roomcnt</th>\n",
" <th>threequarterbathnbr</th>\n",
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" <th>numberofstories</th>\n",
" <th>structuretaxvaluedollarcnt</th>\n",
" <th>taxvaluedollarcnt</th>\n",
" <th>assessmentyear</th>\n",
" <th>landtaxvaluedollarcnt</th>\n",
" <th>taxamount</th>\n",
" <th>censustractandblock</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
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" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
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" <td>2.0</td>\n",
" <td>34144442.0</td>\n",
" <td>-118654084.0</td>\n",
" <td>85768.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>010D</td>\n",
" <td>269.0</td>\n",
" <td>NaN</td>\n",
" <td>6.037800e+07</td>\n",
" <td>37688.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96337.0</td>\n",
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" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>9.0</td>\n",
" <td>2015.0</td>\n",
" <td>9.0</td>\n",
" <td>3991.78</td>\n",
" <td>6.037572e+13</td>\n",
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" <tr>\n",
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" <td>10759547</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34140430.0</td>\n",
" <td>-118625364.0</td>\n",
" <td>4083.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>0109</td>\n",
" <td>261.0</td>\n",
" <td>LCA11*</td>\n",
" <td>6.037800e+07</td>\n",
" <td>37688.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
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" <tr>\n",
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" <td>0.0</td>\n",
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" <td>1539.0</td>\n",
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" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1200</td>\n",
" <td>47.0</td>\n",
" <td>LAC2</td>\n",
" <td>6.037703e+07</td>\n",
" <td>51617.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
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" <td>1.0</td>\n",
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" <td>1963.0</td>\n",
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" <td>650756.0</td>\n",
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" <td>2015.0</td>\n",
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" <td>20800.37</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>10859147</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>5068.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34148863.0</td>\n",
" <td>-118437206.0</td>\n",
" <td>7521.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1200</td>\n",
" <td>47.0</td>\n",
" <td>LAC2</td>\n",
" <td>6.037141e+07</td>\n",
" <td>12447.0</td>\n",
" <td>3101.0</td>\n",
" <td>27080.0</td>\n",
" <td>96424.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1948.0</td>\n",
" <td>1.0</td>\n",
" <td>571346.0</td>\n",
" <td>1156834.0</td>\n",
" <td>2015.0</td>\n",
" <td>585488.0</td>\n",
" <td>14557.57</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>10879947</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1776.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34194168.0</td>\n",
" <td>-118385816.0</td>\n",
" <td>8512.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1210</td>\n",
" <td>31.0</td>\n",
" <td>LAM1</td>\n",
" <td>6.037123e+07</td>\n",
" <td>12447.0</td>\n",
" <td>3101.0</td>\n",
" <td>46795.0</td>\n",
" <td>96450.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1947.0</td>\n",
" <td>1.0</td>\n",
" <td>193796.0</td>\n",
" <td>433491.0</td>\n",
" <td>2015.0</td>\n",
" <td>239695.0</td>\n",
" <td>5725.17</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>10898347</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>2400.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34171873.0</td>\n",
" <td>-118380906.0</td>\n",
" <td>2500.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1210</td>\n",
" <td>31.0</td>\n",
" <td>LAC4</td>\n",
" <td>6.037125e+07</td>\n",
" <td>12447.0</td>\n",
" <td>3101.0</td>\n",
" <td>46795.0</td>\n",
" <td>96446.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1943.0</td>\n",
" <td>1.0</td>\n",
" <td>176383.0</td>\n",
" <td>283315.0</td>\n",
" <td>2015.0</td>\n",
" <td>106932.0</td>\n",
" <td>3661.28</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>10933547</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34131929.0</td>\n",
" <td>-118351474.0</td>\n",
" <td>7000.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>010V</td>\n",
" <td>260.0</td>\n",
" <td>LAC2</td>\n",
" <td>6.037144e+07</td>\n",
" <td>12447.0</td>\n",
" <td>3101.0</td>\n",
" <td>274049.0</td>\n",
" <td>96049.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>397945.0</td>\n",
" <td>554573.0</td>\n",
" <td>2015.0</td>\n",
" <td>156628.0</td>\n",
" <td>6773.34</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>10940747</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>3611.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34171345.0</td>\n",
" <td>-118314900.0</td>\n",
" <td>5333.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1210</td>\n",
" <td>31.0</td>\n",
" <td>BUC4YY</td>\n",
" <td>6.037311e+07</td>\n",
" <td>396054.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96434.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1946.0</td>\n",
" <td>1.0</td>\n",
" <td>101998.0</td>\n",
" <td>688486.0</td>\n",
" <td>2015.0</td>\n",
" <td>586488.0</td>\n",
" <td>7857.84</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>10954547</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34218210.0</td>\n",
" <td>-118331311.0</td>\n",
" <td>145865.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>010D</td>\n",
" <td>269.0</td>\n",
" <td>BUR1*</td>\n",
" <td>6.037310e+07</td>\n",
" <td>396054.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96436.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>9.0</td>\n",
" <td>2015.0</td>\n",
" <td>9.0</td>\n",
" <td>3991.78</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>10976347</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>3754.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34289776.0</td>\n",
" <td>-118432085.0</td>\n",
" <td>7494.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1210</td>\n",
" <td>31.0</td>\n",
" <td>SFC2*</td>\n",
" <td>6.037320e+07</td>\n",
" <td>47547.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96366.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1978.0</td>\n",
" <td>1.0</td>\n",
" <td>218440.0</td>\n",
" <td>261201.0</td>\n",
" <td>2015.0</td>\n",
" <td>42761.0</td>\n",
" <td>4054.76</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>11073947</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>2470.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34265214.0</td>\n",
" <td>-118520217.0</td>\n",
" <td>3423.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1200</td>\n",
" <td>47.0</td>\n",
" <td>LAC2</td>\n",
" <td>6.037111e+07</td>\n",
" <td>12447.0</td>\n",
" <td>3101.0</td>\n",
" <td>31817.0</td>\n",
" <td>96370.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1958.0</td>\n",
" <td>1.0</td>\n",
" <td>245834.0</td>\n",
" <td>430208.0</td>\n",
" <td>2015.0</td>\n",
" <td>184374.0</td>\n",
" <td>6014.18</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>11114347</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34447747.0</td>\n",
" <td>-118565056.0</td>\n",
" <td>81293.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>010D</td>\n",
" <td>269.0</td>\n",
" <td>SCUR3</td>\n",
" <td>6.037920e+07</td>\n",
" <td>25218.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96377.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>9.0</td>\n",
" <td>2015.0</td>\n",
" <td>9.0</td>\n",
" <td>3991.78</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>11116947</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34465048.0</td>\n",
" <td>-118568166.0</td>\n",
" <td>6286.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>010D</td>\n",
" <td>269.0</td>\n",
" <td>LCA25*</td>\n",
" <td>6.037920e+07</td>\n",
" <td>25218.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96377.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>171200.0</td>\n",
" <td>2015.0</td>\n",
" <td>171200.0</td>\n",
" <td>4690.68</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>11142747</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34416889.0</td>\n",
" <td>-118505805.0</td>\n",
" <td>7000.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>300V</td>\n",
" <td>266.0</td>\n",
" <td>SCBP</td>\n",
" <td>6.037920e+07</td>\n",
" <td>54311.0</td>\n",
" <td>3101.0</td>\n",
" <td>37739.0</td>\n",
" <td>96373.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>4265.0</td>\n",
" <td>2015.0</td>\n",
" <td>4265.0</td>\n",
" <td>3991.78</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>11193347</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34585014.0</td>\n",
" <td>-118162010.0</td>\n",
" <td>11975.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>0100</td>\n",
" <td>261.0</td>\n",
" <td>PDA1*</td>\n",
" <td>6.037910e+07</td>\n",
" <td>40227.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>97329.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>10.0</td>\n",
" <td>2015.0</td>\n",
" <td>10.0</td>\n",
" <td>3991.78</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>11215747</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34563376.0</td>\n",
" <td>-118019104.0</td>\n",
" <td>9403.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>0100</td>\n",
" <td>261.0</td>\n",
" <td>PDA21*</td>\n",
" <td>6.037911e+07</td>\n",
" <td>40227.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>97330.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>10.0</td>\n",
" <td>2015.0</td>\n",
" <td>10.0</td>\n",
" <td>3991.78</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>11229347</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34526913.0</td>\n",
" <td>-118050581.0</td>\n",
" <td>3817.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>0100</td>\n",
" <td>261.0</td>\n",
" <td>LCA21*</td>\n",
" <td>6.037911e+07</td>\n",
" <td>40227.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>97330.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>2077.0</td>\n",
" <td>2015.0</td>\n",
" <td>2077.0</td>\n",
" <td>174.21</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>11287347</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>2760.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34690736.0</td>\n",
" <td>-118135225.0</td>\n",
" <td>8856.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1210</td>\n",
" <td>31.0</td>\n",
" <td>LRC3*</td>\n",
" <td>6.037901e+07</td>\n",
" <td>5534.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>97317.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1949.0</td>\n",
" <td>1.0</td>\n",
" <td>32654.0</td>\n",
" <td>62424.0</td>\n",
" <td>2015.0</td>\n",
" <td>29770.0</td>\n",
" <td>2330.24</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>11288547</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>4000.0</td>\n",
" <td>4000.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34733960.0</td>\n",
" <td>-118139298.0</td>\n",
" <td>46526.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>300V</td>\n",
" <td>260.0</td>\n",
" <td>LCM*</td>\n",
" <td>6.037900e+07</td>\n",
" <td>5534.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>97318.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1956.0</td>\n",
" <td>1.0</td>\n",
" <td>56736.0</td>\n",
" <td>102385.0</td>\n",
" <td>2015.0</td>\n",
" <td>45649.0</td>\n",
" <td>4162.56</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>11324547</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>2.0</td>\n",
" <td>3633.0</td>\n",
" <td>3633.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34560018.0</td>\n",
" <td>-118169806.0</td>\n",
" <td>9826.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>0100</td>\n",
" <td>261.0</td>\n",
" <td>LCA22</td>\n",
" <td>6.037910e+07</td>\n",
" <td>40227.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>97329.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>2005.0</td>\n",
" <td>1.0</td>\n",
" <td>218982.0</td>\n",
" <td>291973.0</td>\n",
" <td>2015.0</td>\n",
" <td>72991.0</td>\n",
" <td>6941.39</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>11391347</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>4053.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>33986910.0</td>\n",
" <td>-118329553.0</td>\n",
" <td>8050.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1210</td>\n",
" <td>31.0</td>\n",
" <td>LAC2</td>\n",
" <td>6.037235e+07</td>\n",
" <td>12447.0</td>\n",
" <td>3101.0</td>\n",
" <td>115729.0</td>\n",
" <td>96024.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1957.0</td>\n",
" <td>1.0</td>\n",
" <td>197599.0</td>\n",
" <td>503752.0</td>\n",
" <td>2015.0</td>\n",
" <td>306153.0</td>\n",
" <td>6840.34</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>11395747</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1442.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>33960238.0</td>\n",
" <td>-118319986.0</td>\n",
" <td>2904.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1210</td>\n",
" <td>31.0</td>\n",
" <td>INC2*</td>\n",
" <td>6.037601e+07</td>\n",
" <td>45888.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96137.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>35876.0</td>\n",
" <td>49928.0</td>\n",
" <td>2015.0</td>\n",
" <td>14052.0</td>\n",
" <td>1522.08</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>11404347</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1936.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>33959896.0</td>\n",
" <td>-118350438.0</td>\n",
" <td>1821.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1210</td>\n",
" <td>31.0</td>\n",
" <td>INC1*</td>\n",
" <td>6.037601e+07</td>\n",
" <td>45888.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96133.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1939.0</td>\n",
" <td>1.0</td>\n",
" <td>69879.0</td>\n",
" <td>231720.0</td>\n",
" <td>2015.0</td>\n",
" <td>161841.0</td>\n",
" <td>3703.54</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>11405747</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1606.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>7.0</td>\n",
" <td>33952952.0</td>\n",
" <td>-118361711.0</td>\n",
" <td>5231.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1210</td>\n",
" <td>31.0</td>\n",
" <td>INC2YY</td>\n",
" <td>6.037601e+07</td>\n",
" <td>45888.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96133.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1926.0</td>\n",
" <td>1.0</td>\n",
" <td>41917.0</td>\n",
" <td>181667.0</td>\n",
" <td>2015.0</td>\n",
" <td>139750.0</td>\n",
" <td>2992.02</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>11417147</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>2820.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>33931500.0</td>\n",
" <td>-118352104.0</td>\n",
" <td>5934.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1210</td>\n",
" <td>31.0</td>\n",
" <td>HAC2YY</td>\n",
" <td>6.037602e+07</td>\n",
" <td>45888.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96136.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>1938.0</td>\n",
" <td>1.0</td>\n",
" <td>44959.0</td>\n",
" <td>133717.0</td>\n",
" <td>2015.0</td>\n",
" <td>88758.0</td>\n",
" <td>2797.70</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>11457547</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>33961232.0</td>\n",
" <td>-118385376.0</td>\n",
" <td>500.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>0100</td>\n",
" <td>261.0</td>\n",
" <td>LAR2</td>\n",
" <td>6.037276e+07</td>\n",
" <td>12447.0</td>\n",
" <td>3101.0</td>\n",
" <td>7877.0</td>\n",
" <td>96026.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>124.0</td>\n",
" <td>2015.0</td>\n",
" <td>124.0</td>\n",
" <td>3991.78</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>11488147</td>\n",
" <td>1.0</td>\n",
" <td>4.0</td>\n",
" <td>5.0</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>2865.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>4.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>33879216.0</td>\n",
" <td>-118361434.0</td>\n",
" <td>4990.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>0200</td>\n",
" <td>246.0</td>\n",
" <td>RBR-3</td>\n",
" <td>6.037621e+07</td>\n",
" <td>33612.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96124.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>1972.0</td>\n",
" <td>1.0</td>\n",
" <td>267623.0</td>\n",
" <td>818739.0</td>\n",
" <td>2015.0</td>\n",
" <td>551116.0</td>\n",
" <td>10455.41</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>11520747</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>6790.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34016768.0</td>\n",
" <td>-118408671.0</td>\n",
" <td>10437.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1200</td>\n",
" <td>47.0</td>\n",
" <td>CCR4*</td>\n",
" <td>6.037703e+07</td>\n",
" <td>51617.0</td>\n",
" <td>3101.0</td>\n",
" <td>762191.0</td>\n",
" <td>96097.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1955.0</td>\n",
" <td>1.0</td>\n",
" <td>204800.0</td>\n",
" <td>786584.0</td>\n",
" <td>2015.0</td>\n",
" <td>581784.0</td>\n",
" <td>11304.81</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>11524947</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>4.0</td>\n",
" <td>2.0</td>\n",
" <td>1090.0</td>\n",
" <td>1090.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>33974100.0</td>\n",
" <td>-118423000.0</td>\n",
" <td>40247.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>010C</td>\n",
" <td>266.0</td>\n",
" <td>LAC2(PV)</td>\n",
" <td>6.037276e+07</td>\n",
" <td>12447.0</td>\n",
" <td>3101.0</td>\n",
" <td>13327.0</td>\n",
" <td>96072.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>2004.0</td>\n",
" <td>1.0</td>\n",
" <td>229399.0</td>\n",
" <td>352198.0</td>\n",
" <td>2015.0</td>\n",
" <td>122799.0</td>\n",
" <td>6165.36</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>11544747</td>\n",
" <td>1.0</td>\n",
" <td>4.0</td>\n",
" <td>3.0</td>\n",
" <td>10.0</td>\n",
" <td>4.0</td>\n",
" <td>1620.0</td>\n",
" <td>1620.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>4.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>33996200.0</td>\n",
" <td>-118438000.0</td>\n",
" <td>7000.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>0100</td>\n",
" <td>261.0</td>\n",
" <td>LAR3</td>\n",
" <td>6.037272e+07</td>\n",
" <td>12447.0</td>\n",
" <td>3101.0</td>\n",
" <td>116415.0</td>\n",
" <td>96047.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>2011.0</td>\n",
" <td>1.0</td>\n",
" <td>334432.0</td>\n",
" <td>835036.0</td>\n",
" <td>2015.0</td>\n",
" <td>500604.0</td>\n",
" <td>10244.94</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2985187</th>\n",
" <td>167636430</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34008249.0</td>\n",
" <td>-118172540.5</td>\n",
" <td>7000.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>261.0</td>\n",
" <td>NaN</td>\n",
" <td>6.037571e+07</td>\n",
" <td>25218.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96377.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>306086.0</td>\n",
" <td>2015.0</td>\n",
" <td>167042.0</td>\n",
" <td>3991.78</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2985188</th>\n",
" <td>167690630</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34008249.0</td>\n",
" <td>-118172540.5</td>\n",
" <td>7000.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>261.0</td>\n",
" <td>NaN</td>\n",
" <td>6.037571e+07</td>\n",
" <td>25218.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96377.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>306086.0</td>\n",
" <td>2015.0</td>\n",
" <td>167042.0</td>\n",
" <td>3991.78</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2985189</th>\n",
" <td>167636630</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34008249.0</td>\n",
" <td>-118172540.5</td>\n",
" <td>7000.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>261.0</td>\n",
" <td>NaN</td>\n",
" <td>6.037571e+07</td>\n",
" <td>25218.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96377.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>306086.0</td>\n",
" <td>2015.0</td>\n",
" <td>167042.0</td>\n",
" <td>3991.78</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2985190</th>\n",
" <td>10834030</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34008249.0</td>\n",
" <td>-118172540.5</td>\n",
" <td>7000.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>261.0</td>\n",
" <td>NaN</td>\n",
" <td>6.037571e+07</td>\n",
" <td>25218.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96377.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>306086.0</td>\n",
" <td>2015.0</td>\n",
" <td>167042.0</td>\n",
" <td>3991.78</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2985191</th>\n",
" <td>167637430</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34008249.0</td>\n",
" <td>-118172540.5</td>\n",
" <td>7000.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>261.0</td>\n",
" <td>NaN</td>\n",
" <td>6.037571e+07</td>\n",
" <td>25218.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96377.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>306086.0</td>\n",
" <td>2015.0</td>\n",
" <td>167042.0</td>\n",
" <td>3991.78</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2985192</th>\n",
" <td>167637630</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34008249.0</td>\n",
" <td>-118172540.5</td>\n",
" <td>7000.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>261.0</td>\n",
" <td>NaN</td>\n",
" <td>6.037571e+07</td>\n",
" <td>25218.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96377.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>306086.0</td>\n",
" <td>2015.0</td>\n",
" <td>167042.0</td>\n",
" <td>3991.78</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2985193</th>\n",
" <td>167637230</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34008249.0</td>\n",
" <td>-118172540.5</td>\n",
" <td>7000.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>261.0</td>\n",
" <td>NaN</td>\n",
" <td>6.037571e+07</td>\n",
" <td>25218.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96377.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>306086.0</td>\n",
" <td>2015.0</td>\n",
" <td>167042.0</td>\n",
" <td>3991.78</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2985194</th>\n",
" <td>11645030</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34008249.0</td>\n",
" <td>-118172540.5</td>\n",
" <td>7000.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>261.0</td>\n",
" <td>NaN</td>\n",
" <td>6.037571e+07</td>\n",
" <td>25218.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96377.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>306086.0</td>\n",
" <td>2015.0</td>\n",
" <td>167042.0</td>\n",
" <td>3991.78</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2985195</th>\n",
" <td>167689030</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34008249.0</td>\n",
" <td>-118172540.5</td>\n",
" <td>7000.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>261.0</td>\n",
" <td>NaN</td>\n",
" <td>6.037571e+07</td>\n",
" <td>25218.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96377.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>306086.0</td>\n",
" <td>2015.0</td>\n",
" <td>167042.0</td>\n",
" <td>3991.78</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2985196</th>\n",
" <td>167638630</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34008249.0</td>\n",
" <td>-118172540.5</td>\n",
" <td>7000.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>261.0</td>\n",
" <td>NaN</td>\n",
" <td>6.037571e+07</td>\n",
" <td>25218.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96377.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>306086.0</td>\n",
" <td>2015.0</td>\n",
" <td>167042.0</td>\n",
" <td>3991.78</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2985197</th>\n",
" <td>167638430</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34008249.0</td>\n",
" <td>-118172540.5</td>\n",
" <td>7000.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>261.0</td>\n",
" <td>NaN</td>\n",
" <td>6.037571e+07</td>\n",
" <td>25218.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96377.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>306086.0</td>\n",
" <td>2015.0</td>\n",
" <td>167042.0</td>\n",
" <td>3991.78</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2985198</th>\n",
" <td>14342030</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34008249.0</td>\n",
" <td>-118172540.5</td>\n",
" <td>7000.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>261.0</td>\n",
" <td>NaN</td>\n",
" <td>6.037571e+07</td>\n",
" <td>25218.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96377.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>306086.0</td>\n",
" <td>2015.0</td>\n",
" <td>167042.0</td>\n",
" <td>3991.78</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2985199</th>\n",
" <td>167638230</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34008249.0</td>\n",
" <td>-118172540.5</td>\n",
" <td>7000.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>261.0</td>\n",
" <td>NaN</td>\n",
" <td>6.037571e+07</td>\n",
" <td>25218.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96377.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>306086.0</td>\n",
" <td>2015.0</td>\n",
" <td>167042.0</td>\n",
" <td>3991.78</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2985200</th>\n",
" <td>167637830</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34008249.0</td>\n",
" <td>-118172540.5</td>\n",
" <td>7000.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>261.0</td>\n",
" <td>NaN</td>\n",
" <td>6.037571e+07</td>\n",
" <td>25218.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96377.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>306086.0</td>\n",
" <td>2015.0</td>\n",
" <td>167042.0</td>\n",
" <td>3991.78</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2985201</th>\n",
" <td>167639230</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34008249.0</td>\n",
" <td>-118172540.5</td>\n",
" <td>7000.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>261.0</td>\n",
" <td>NaN</td>\n",
" <td>6.037571e+07</td>\n",
" <td>25218.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96377.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>306086.0</td>\n",
" <td>2015.0</td>\n",
" <td>167042.0</td>\n",
" <td>3991.78</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2985202</th>\n",
" <td>14341030</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34008249.0</td>\n",
" <td>-118172540.5</td>\n",
" <td>7000.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>261.0</td>\n",
" <td>NaN</td>\n",
" <td>6.037571e+07</td>\n",
" <td>25218.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96377.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>306086.0</td>\n",
" <td>2015.0</td>\n",
" <td>167042.0</td>\n",
" <td>3991.78</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2985203</th>\n",
" <td>14341630</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34008249.0</td>\n",
" <td>-118172540.5</td>\n",
" <td>7000.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>261.0</td>\n",
" <td>NaN</td>\n",
" <td>6.037571e+07</td>\n",
" <td>25218.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96377.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>306086.0</td>\n",
" <td>2015.0</td>\n",
" <td>167042.0</td>\n",
" <td>3991.78</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2985204</th>\n",
" <td>14367630</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34008249.0</td>\n",
" <td>-118172540.5</td>\n",
" <td>7000.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>261.0</td>\n",
" <td>NaN</td>\n",
" <td>6.037571e+07</td>\n",
" <td>25218.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96377.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>306086.0</td>\n",
" <td>2015.0</td>\n",
" <td>167042.0</td>\n",
" <td>3991.78</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2985205</th>\n",
" <td>167638830</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34008249.0</td>\n",
" <td>-118172540.5</td>\n",
" <td>7000.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>261.0</td>\n",
" <td>NaN</td>\n",
" <td>6.037571e+07</td>\n",
" <td>25218.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96377.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>306086.0</td>\n",
" <td>2015.0</td>\n",
" <td>167042.0</td>\n",
" <td>3991.78</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2985206</th>\n",
" <td>12572230</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34008249.0</td>\n",
" <td>-118172540.5</td>\n",
" <td>7000.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>261.0</td>\n",
" <td>NaN</td>\n",
" <td>6.037571e+07</td>\n",
" <td>25218.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96377.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>306086.0</td>\n",
" <td>2015.0</td>\n",
" <td>167042.0</td>\n",
" <td>3991.78</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2985207</th>\n",
" <td>14460030</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34008249.0</td>\n",
" <td>-118172540.5</td>\n",
" <td>7000.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>261.0</td>\n",
" <td>NaN</td>\n",
" <td>6.037571e+07</td>\n",
" <td>25218.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96377.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>306086.0</td>\n",
" <td>2015.0</td>\n",
" <td>167042.0</td>\n",
" <td>3991.78</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2985208</th>\n",
" <td>14284830</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34008249.0</td>\n",
" <td>-118172540.5</td>\n",
" <td>7000.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>261.0</td>\n",
" <td>NaN</td>\n",
" <td>6.037571e+07</td>\n",
" <td>25218.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96377.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>306086.0</td>\n",
" <td>2015.0</td>\n",
" <td>167042.0</td>\n",
" <td>3991.78</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2985209</th>\n",
" <td>14285230</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34008249.0</td>\n",
" <td>-118172540.5</td>\n",
" <td>7000.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>261.0</td>\n",
" <td>NaN</td>\n",
" <td>6.037571e+07</td>\n",
" <td>25218.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96377.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>306086.0</td>\n",
" <td>2015.0</td>\n",
" <td>167042.0</td>\n",
" <td>3991.78</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2985210</th>\n",
" <td>14455630</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34008249.0</td>\n",
" <td>-118172540.5</td>\n",
" <td>7000.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>261.0</td>\n",
" <td>NaN</td>\n",
" <td>6.037571e+07</td>\n",
" <td>25218.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96377.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>306086.0</td>\n",
" <td>2015.0</td>\n",
" <td>167042.0</td>\n",
" <td>3991.78</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2985211</th>\n",
" <td>11117630</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34008249.0</td>\n",
" <td>-118172540.5</td>\n",
" <td>7000.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>261.0</td>\n",
" <td>NaN</td>\n",
" <td>6.037571e+07</td>\n",
" <td>25218.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96377.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>306086.0</td>\n",
" <td>2015.0</td>\n",
" <td>167042.0</td>\n",
" <td>3991.78</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2985212</th>\n",
" <td>168176230</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34008249.0</td>\n",
" <td>-118172540.5</td>\n",
" <td>7000.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>261.0</td>\n",
" <td>NaN</td>\n",
" <td>6.037571e+07</td>\n",
" <td>25218.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96377.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>306086.0</td>\n",
" <td>2015.0</td>\n",
" <td>167042.0</td>\n",
" <td>3991.78</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2985213</th>\n",
" <td>14273630</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34008249.0</td>\n",
" <td>-118172540.5</td>\n",
" <td>7000.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>261.0</td>\n",
" <td>NaN</td>\n",
" <td>6.037571e+07</td>\n",
" <td>25218.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96377.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>306086.0</td>\n",
" <td>2015.0</td>\n",
" <td>167042.0</td>\n",
" <td>3991.78</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2985214</th>\n",
" <td>168040630</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34008249.0</td>\n",
" <td>-118172540.5</td>\n",
" <td>7000.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>261.0</td>\n",
" <td>NaN</td>\n",
" <td>6.037571e+07</td>\n",
" <td>25218.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96377.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>306086.0</td>\n",
" <td>2015.0</td>\n",
" <td>167042.0</td>\n",
" <td>3991.78</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2985215</th>\n",
" <td>168040830</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34008249.0</td>\n",
" <td>-118172540.5</td>\n",
" <td>7000.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>261.0</td>\n",
" <td>NaN</td>\n",
" <td>6.037571e+07</td>\n",
" <td>25218.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96377.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>306086.0</td>\n",
" <td>2015.0</td>\n",
" <td>167042.0</td>\n",
" <td>3991.78</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2985216</th>\n",
" <td>168040430</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>1572.0</td>\n",
" <td>1539.0</td>\n",
" <td>6037.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>441.0</td>\n",
" <td>2.0</td>\n",
" <td>34008249.0</td>\n",
" <td>-118172540.5</td>\n",
" <td>7000.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>261.0</td>\n",
" <td>NaN</td>\n",
" <td>6.037571e+07</td>\n",
" <td>25218.0</td>\n",
" <td>3101.0</td>\n",
" <td>118920.0</td>\n",
" <td>96377.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>1963.0</td>\n",
" <td>1.0</td>\n",
" <td>122590.0</td>\n",
" <td>306086.0</td>\n",
" <td>2015.0</td>\n",
" <td>167042.0</td>\n",
" <td>3991.78</td>\n",
" <td>6.037572e+13</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>2985217 rows × 38 columns</p>\n",
"</div>"
],
"text/plain": [
" parcelid airconditioningtypeid bathroomcnt bedroomcnt \\\n",
"0 10754147 1.0 0.0 0.0 \n",
"1 10759547 1.0 0.0 0.0 \n",
"2 10843547 1.0 0.0 0.0 \n",
"3 10859147 1.0 0.0 0.0 \n",
"4 10879947 1.0 0.0 0.0 \n",
"5 10898347 1.0 0.0 0.0 \n",
"6 10933547 1.0 0.0 0.0 \n",
"7 10940747 1.0 0.0 0.0 \n",
"8 10954547 1.0 0.0 0.0 \n",
"9 10976347 1.0 0.0 0.0 \n",
"10 11073947 1.0 0.0 0.0 \n",
"11 11114347 1.0 0.0 0.0 \n",
"12 11116947 1.0 0.0 0.0 \n",
"13 11142747 1.0 0.0 0.0 \n",
"14 11193347 1.0 0.0 0.0 \n",
"15 11215747 1.0 0.0 0.0 \n",
"16 11229347 1.0 0.0 0.0 \n",
"17 11287347 1.0 0.0 0.0 \n",
"18 11288547 1.0 0.0 0.0 \n",
"19 11324547 1.0 2.0 4.0 \n",
"20 11391347 1.0 0.0 0.0 \n",
"21 11395747 1.0 0.0 0.0 \n",
"22 11404347 1.0 0.0 0.0 \n",
"23 11405747 1.0 0.0 0.0 \n",
"24 11417147 1.0 0.0 0.0 \n",
"25 11457547 1.0 0.0 0.0 \n",
"26 11488147 1.0 4.0 5.0 \n",
"27 11520747 1.0 0.0 0.0 \n",
"28 11524947 1.0 2.0 2.0 \n",
"29 11544747 1.0 4.0 3.0 \n",
"... ... ... ... ... \n",
"2985187 167636430 1.0 2.0 3.0 \n",
"2985188 167690630 1.0 2.0 3.0 \n",
"2985189 167636630 1.0 2.0 3.0 \n",
"2985190 10834030 1.0 2.0 3.0 \n",
"2985191 167637430 1.0 2.0 3.0 \n",
"2985192 167637630 1.0 2.0 3.0 \n",
"2985193 167637230 1.0 2.0 3.0 \n",
"2985194 11645030 1.0 2.0 3.0 \n",
"2985195 167689030 1.0 2.0 3.0 \n",
"2985196 167638630 1.0 2.0 3.0 \n",
"2985197 167638430 1.0 2.0 3.0 \n",
"2985198 14342030 1.0 2.0 3.0 \n",
"2985199 167638230 1.0 2.0 3.0 \n",
"2985200 167637830 1.0 2.0 3.0 \n",
"2985201 167639230 1.0 2.0 3.0 \n",
"2985202 14341030 1.0 2.0 3.0 \n",
"2985203 14341630 1.0 2.0 3.0 \n",
"2985204 14367630 1.0 2.0 3.0 \n",
"2985205 167638830 1.0 2.0 3.0 \n",
"2985206 12572230 1.0 2.0 3.0 \n",
"2985207 14460030 1.0 2.0 3.0 \n",
"2985208 14284830 1.0 2.0 3.0 \n",
"2985209 14285230 1.0 2.0 3.0 \n",
"2985210 14455630 1.0 2.0 3.0 \n",
"2985211 11117630 1.0 2.0 3.0 \n",
"2985212 168176230 1.0 2.0 3.0 \n",
"2985213 14273630 1.0 2.0 3.0 \n",
"2985214 168040630 1.0 2.0 3.0 \n",
"2985215 168040830 1.0 2.0 3.0 \n",
"2985216 168040430 1.0 2.0 3.0 \n",
"\n",
" buildingqualitytypeid calculatedbathnbr \\\n",
"0 7.0 2.0 \n",
"1 7.0 2.0 \n",
"2 7.0 2.0 \n",
"3 7.0 2.0 \n",
"4 7.0 2.0 \n",
"5 7.0 2.0 \n",
"6 7.0 2.0 \n",
"7 7.0 2.0 \n",
"8 7.0 2.0 \n",
"9 7.0 2.0 \n",
"10 7.0 2.0 \n",
"11 7.0 2.0 \n",
"12 7.0 2.0 \n",
"13 7.0 2.0 \n",
"14 7.0 2.0 \n",
"15 7.0 2.0 \n",
"16 7.0 2.0 \n",
"17 7.0 2.0 \n",
"18 7.0 2.0 \n",
"19 4.0 2.0 \n",
"20 7.0 2.0 \n",
"21 7.0 2.0 \n",
"22 7.0 2.0 \n",
"23 7.0 2.0 \n",
"24 7.0 2.0 \n",
"25 7.0 2.0 \n",
"26 4.0 4.0 \n",
"27 7.0 2.0 \n",
"28 4.0 2.0 \n",
"29 10.0 4.0 \n",
"... ... ... \n",
"2985187 7.0 2.0 \n",
"2985188 7.0 2.0 \n",
"2985189 7.0 2.0 \n",
"2985190 7.0 2.0 \n",
"2985191 7.0 2.0 \n",
"2985192 7.0 2.0 \n",
"2985193 7.0 2.0 \n",
"2985194 7.0 2.0 \n",
"2985195 7.0 2.0 \n",
"2985196 7.0 2.0 \n",
"2985197 7.0 2.0 \n",
"2985198 7.0 2.0 \n",
"2985199 7.0 2.0 \n",
"2985200 7.0 2.0 \n",
"2985201 7.0 2.0 \n",
"2985202 7.0 2.0 \n",
"2985203 7.0 2.0 \n",
"2985204 7.0 2.0 \n",
"2985205 7.0 2.0 \n",
"2985206 7.0 2.0 \n",
"2985207 7.0 2.0 \n",
"2985208 7.0 2.0 \n",
"2985209 7.0 2.0 \n",
"2985210 7.0 2.0 \n",
"2985211 7.0 2.0 \n",
"2985212 7.0 2.0 \n",
"2985213 7.0 2.0 \n",
"2985214 7.0 2.0 \n",
"2985215 7.0 2.0 \n",
"2985216 7.0 2.0 \n",
"\n",
" calculatedfinishedsquarefeet finishedsquarefeet12 fips \\\n",
"0 1572.0 1539.0 6037.0 \n",
"1 1572.0 1539.0 6037.0 \n",
"2 73026.0 1539.0 6037.0 \n",
"3 5068.0 1539.0 6037.0 \n",
"4 1776.0 1539.0 6037.0 \n",
"5 2400.0 1539.0 6037.0 \n",
"6 1572.0 1539.0 6037.0 \n",
"7 3611.0 1539.0 6037.0 \n",
"8 1572.0 1539.0 6037.0 \n",
"9 3754.0 1539.0 6037.0 \n",
"10 2470.0 1539.0 6037.0 \n",
"11 1572.0 1539.0 6037.0 \n",
"12 1572.0 1539.0 6037.0 \n",
"13 1572.0 1539.0 6037.0 \n",
"14 1572.0 1539.0 6037.0 \n",
"15 1572.0 1539.0 6037.0 \n",
"16 1572.0 1539.0 6037.0 \n",
"17 2760.0 1539.0 6037.0 \n",
"18 4000.0 4000.0 6037.0 \n",
"19 3633.0 3633.0 6037.0 \n",
"20 4053.0 1539.0 6037.0 \n",
"21 1442.0 1539.0 6037.0 \n",
"22 1936.0 1539.0 6037.0 \n",
"23 1606.0 1539.0 6037.0 \n",
"24 2820.0 1539.0 6037.0 \n",
"25 1572.0 1539.0 6037.0 \n",
"26 2865.0 1539.0 6037.0 \n",
"27 6790.0 1539.0 6037.0 \n",
"28 1090.0 1090.0 6037.0 \n",
"29 1620.0 1620.0 6037.0 \n",
"... ... ... ... \n",
"2985187 1572.0 1539.0 6037.0 \n",
"2985188 1572.0 1539.0 6037.0 \n",
"2985189 1572.0 1539.0 6037.0 \n",
"2985190 1572.0 1539.0 6037.0 \n",
"2985191 1572.0 1539.0 6037.0 \n",
"2985192 1572.0 1539.0 6037.0 \n",
"2985193 1572.0 1539.0 6037.0 \n",
"2985194 1572.0 1539.0 6037.0 \n",
"2985195 1572.0 1539.0 6037.0 \n",
"2985196 1572.0 1539.0 6037.0 \n",
"2985197 1572.0 1539.0 6037.0 \n",
"2985198 1572.0 1539.0 6037.0 \n",
"2985199 1572.0 1539.0 6037.0 \n",
"2985200 1572.0 1539.0 6037.0 \n",
"2985201 1572.0 1539.0 6037.0 \n",
"2985202 1572.0 1539.0 6037.0 \n",
"2985203 1572.0 1539.0 6037.0 \n",
"2985204 1572.0 1539.0 6037.0 \n",
"2985205 1572.0 1539.0 6037.0 \n",
"2985206 1572.0 1539.0 6037.0 \n",
"2985207 1572.0 1539.0 6037.0 \n",
"2985208 1572.0 1539.0 6037.0 \n",
"2985209 1572.0 1539.0 6037.0 \n",
"2985210 1572.0 1539.0 6037.0 \n",
"2985211 1572.0 1539.0 6037.0 \n",
"2985212 1572.0 1539.0 6037.0 \n",
"2985213 1572.0 1539.0 6037.0 \n",
"2985214 1572.0 1539.0 6037.0 \n",
"2985215 1572.0 1539.0 6037.0 \n",
"2985216 1572.0 1539.0 6037.0 \n",
"\n",
" fireplacecnt fullbathcnt garagecarcnt garagetotalsqft \\\n",
"0 1.0 2.0 2.0 441.0 \n",
"1 1.0 2.0 2.0 441.0 \n",
"2 1.0 2.0 2.0 441.0 \n",
"3 1.0 2.0 2.0 441.0 \n",
"4 1.0 2.0 2.0 441.0 \n",
"5 1.0 2.0 2.0 441.0 \n",
"6 1.0 2.0 2.0 441.0 \n",
"7 1.0 2.0 2.0 441.0 \n",
"8 1.0 2.0 2.0 441.0 \n",
"9 1.0 2.0 2.0 441.0 \n",
"10 1.0 2.0 2.0 441.0 \n",
"11 1.0 2.0 2.0 441.0 \n",
"12 1.0 2.0 2.0 441.0 \n",
"13 1.0 2.0 2.0 441.0 \n",
"14 1.0 2.0 2.0 441.0 \n",
"15 1.0 2.0 2.0 441.0 \n",
"16 1.0 2.0 2.0 441.0 \n",
"17 1.0 2.0 2.0 441.0 \n",
"18 1.0 2.0 2.0 441.0 \n",
"19 1.0 2.0 2.0 441.0 \n",
"20 1.0 2.0 2.0 441.0 \n",
"21 1.0 2.0 2.0 441.0 \n",
"22 1.0 2.0 2.0 441.0 \n",
"23 1.0 2.0 2.0 441.0 \n",
"24 1.0 2.0 2.0 441.0 \n",
"25 1.0 2.0 2.0 441.0 \n",
"26 1.0 4.0 2.0 441.0 \n",
"27 1.0 2.0 2.0 441.0 \n",
"28 1.0 2.0 2.0 441.0 \n",
"29 1.0 4.0 2.0 441.0 \n",
"... ... ... ... ... \n",
"2985187 1.0 2.0 2.0 441.0 \n",
"2985188 1.0 2.0 2.0 441.0 \n",
"2985189 1.0 2.0 2.0 441.0 \n",
"2985190 1.0 2.0 2.0 441.0 \n",
"2985191 1.0 2.0 2.0 441.0 \n",
"2985192 1.0 2.0 2.0 441.0 \n",
"2985193 1.0 2.0 2.0 441.0 \n",
"2985194 1.0 2.0 2.0 441.0 \n",
"2985195 1.0 2.0 2.0 441.0 \n",
"2985196 1.0 2.0 2.0 441.0 \n",
"2985197 1.0 2.0 2.0 441.0 \n",
"2985198 1.0 2.0 2.0 441.0 \n",
"2985199 1.0 2.0 2.0 441.0 \n",
"2985200 1.0 2.0 2.0 441.0 \n",
"2985201 1.0 2.0 2.0 441.0 \n",
"2985202 1.0 2.0 2.0 441.0 \n",
"2985203 1.0 2.0 2.0 441.0 \n",
"2985204 1.0 2.0 2.0 441.0 \n",
"2985205 1.0 2.0 2.0 441.0 \n",
"2985206 1.0 2.0 2.0 441.0 \n",
"2985207 1.0 2.0 2.0 441.0 \n",
"2985208 1.0 2.0 2.0 441.0 \n",
"2985209 1.0 2.0 2.0 441.0 \n",
"2985210 1.0 2.0 2.0 441.0 \n",
"2985211 1.0 2.0 2.0 441.0 \n",
"2985212 1.0 2.0 2.0 441.0 \n",
"2985213 1.0 2.0 2.0 441.0 \n",
"2985214 1.0 2.0 2.0 441.0 \n",
"2985215 1.0 2.0 2.0 441.0 \n",
"2985216 1.0 2.0 2.0 441.0 \n",
"\n",
" heatingorsystemtypeid latitude longitude lotsizesquarefeet \\\n",
"0 2.0 34144442.0 -118654084.0 85768.0 \n",
"1 2.0 34140430.0 -118625364.0 4083.0 \n",
"2 2.0 33989359.0 -118394633.0 63085.0 \n",
"3 2.0 34148863.0 -118437206.0 7521.0 \n",
"4 2.0 34194168.0 -118385816.0 8512.0 \n",
"5 2.0 34171873.0 -118380906.0 2500.0 \n",
"6 2.0 34131929.0 -118351474.0 7000.0 \n",
"7 2.0 34171345.0 -118314900.0 5333.0 \n",
"8 2.0 34218210.0 -118331311.0 145865.0 \n",
"9 2.0 34289776.0 -118432085.0 7494.0 \n",
"10 2.0 34265214.0 -118520217.0 3423.0 \n",
"11 2.0 34447747.0 -118565056.0 81293.0 \n",
"12 2.0 34465048.0 -118568166.0 6286.0 \n",
"13 2.0 34416889.0 -118505805.0 7000.0 \n",
"14 2.0 34585014.0 -118162010.0 11975.0 \n",
"15 2.0 34563376.0 -118019104.0 9403.0 \n",
"16 2.0 34526913.0 -118050581.0 3817.0 \n",
"17 2.0 34690736.0 -118135225.0 8856.0 \n",
"18 2.0 34733960.0 -118139298.0 46526.0 \n",
"19 2.0 34560018.0 -118169806.0 9826.0 \n",
"20 2.0 33986910.0 -118329553.0 8050.0 \n",
"21 2.0 33960238.0 -118319986.0 2904.0 \n",
"22 2.0 33959896.0 -118350438.0 1821.0 \n",
"23 7.0 33952952.0 -118361711.0 5231.0 \n",
"24 2.0 33931500.0 -118352104.0 5934.0 \n",
"25 2.0 33961232.0 -118385376.0 500.0 \n",
"26 2.0 33879216.0 -118361434.0 4990.0 \n",
"27 2.0 34016768.0 -118408671.0 10437.0 \n",
"28 2.0 33974100.0 -118423000.0 40247.0 \n",
"29 2.0 33996200.0 -118438000.0 7000.0 \n",
"... ... ... ... ... \n",
"2985187 2.0 34008249.0 -118172540.5 7000.0 \n",
"2985188 2.0 34008249.0 -118172540.5 7000.0 \n",
"2985189 2.0 34008249.0 -118172540.5 7000.0 \n",
"2985190 2.0 34008249.0 -118172540.5 7000.0 \n",
"2985191 2.0 34008249.0 -118172540.5 7000.0 \n",
"2985192 2.0 34008249.0 -118172540.5 7000.0 \n",
"2985193 2.0 34008249.0 -118172540.5 7000.0 \n",
"2985194 2.0 34008249.0 -118172540.5 7000.0 \n",
"2985195 2.0 34008249.0 -118172540.5 7000.0 \n",
"2985196 2.0 34008249.0 -118172540.5 7000.0 \n",
"2985197 2.0 34008249.0 -118172540.5 7000.0 \n",
"2985198 2.0 34008249.0 -118172540.5 7000.0 \n",
"2985199 2.0 34008249.0 -118172540.5 7000.0 \n",
"2985200 2.0 34008249.0 -118172540.5 7000.0 \n",
"2985201 2.0 34008249.0 -118172540.5 7000.0 \n",
"2985202 2.0 34008249.0 -118172540.5 7000.0 \n",
"2985203 2.0 34008249.0 -118172540.5 7000.0 \n",
"2985204 2.0 34008249.0 -118172540.5 7000.0 \n",
"2985205 2.0 34008249.0 -118172540.5 7000.0 \n",
"2985206 2.0 34008249.0 -118172540.5 7000.0 \n",
"2985207 2.0 34008249.0 -118172540.5 7000.0 \n",
"2985208 2.0 34008249.0 -118172540.5 7000.0 \n",
"2985209 2.0 34008249.0 -118172540.5 7000.0 \n",
"2985210 2.0 34008249.0 -118172540.5 7000.0 \n",
"2985211 2.0 34008249.0 -118172540.5 7000.0 \n",
"2985212 2.0 34008249.0 -118172540.5 7000.0 \n",
"2985213 2.0 34008249.0 -118172540.5 7000.0 \n",
"2985214 2.0 34008249.0 -118172540.5 7000.0 \n",
"2985215 2.0 34008249.0 -118172540.5 7000.0 \n",
"2985216 2.0 34008249.0 -118172540.5 7000.0 \n",
"\n",
" poolcnt pooltypeid7 propertycountylandusecode \\\n",
"0 1.0 1.0 010D \n",
"1 1.0 1.0 0109 \n",
"2 1.0 1.0 1200 \n",
"3 1.0 1.0 1200 \n",
"4 1.0 1.0 1210 \n",
"5 1.0 1.0 1210 \n",
"6 1.0 1.0 010V \n",
"7 1.0 1.0 1210 \n",
"8 1.0 1.0 010D \n",
"9 1.0 1.0 1210 \n",
"10 1.0 1.0 1200 \n",
"11 1.0 1.0 010D \n",
"12 1.0 1.0 010D \n",
"13 1.0 1.0 300V \n",
"14 1.0 1.0 0100 \n",
"15 1.0 1.0 0100 \n",
"16 1.0 1.0 0100 \n",
"17 1.0 1.0 1210 \n",
"18 1.0 1.0 300V \n",
"19 1.0 1.0 0100 \n",
"20 1.0 1.0 1210 \n",
"21 1.0 1.0 1210 \n",
"22 1.0 1.0 1210 \n",
"23 1.0 1.0 1210 \n",
"24 1.0 1.0 1210 \n",
"25 1.0 1.0 0100 \n",
"26 1.0 1.0 0200 \n",
"27 1.0 1.0 1200 \n",
"28 1.0 1.0 010C \n",
"29 1.0 1.0 0100 \n",
"... ... ... ... \n",
"2985187 1.0 1.0 NaN \n",
"2985188 1.0 1.0 NaN \n",
"2985189 1.0 1.0 NaN \n",
"2985190 1.0 1.0 NaN \n",
"2985191 1.0 1.0 NaN \n",
"2985192 1.0 1.0 NaN \n",
"2985193 1.0 1.0 NaN \n",
"2985194 1.0 1.0 NaN \n",
"2985195 1.0 1.0 NaN \n",
"2985196 1.0 1.0 NaN \n",
"2985197 1.0 1.0 NaN \n",
"2985198 1.0 1.0 NaN \n",
"2985199 1.0 1.0 NaN \n",
"2985200 1.0 1.0 NaN \n",
"2985201 1.0 1.0 NaN \n",
"2985202 1.0 1.0 NaN \n",
"2985203 1.0 1.0 NaN \n",
"2985204 1.0 1.0 NaN \n",
"2985205 1.0 1.0 NaN \n",
"2985206 1.0 1.0 NaN \n",
"2985207 1.0 1.0 NaN \n",
"2985208 1.0 1.0 NaN \n",
"2985209 1.0 1.0 NaN \n",
"2985210 1.0 1.0 NaN \n",
"2985211 1.0 1.0 NaN \n",
"2985212 1.0 1.0 NaN \n",
"2985213 1.0 1.0 NaN \n",
"2985214 1.0 1.0 NaN \n",
"2985215 1.0 1.0 NaN \n",
"2985216 1.0 1.0 NaN \n",
"\n",
" propertylandusetypeid propertyzoningdesc rawcensustractandblock \\\n",
"0 269.0 NaN 6.037800e+07 \n",
"1 261.0 LCA11* 6.037800e+07 \n",
"2 47.0 LAC2 6.037703e+07 \n",
"3 47.0 LAC2 6.037141e+07 \n",
"4 31.0 LAM1 6.037123e+07 \n",
"5 31.0 LAC4 6.037125e+07 \n",
"6 260.0 LAC2 6.037144e+07 \n",
"7 31.0 BUC4YY 6.037311e+07 \n",
"8 269.0 BUR1* 6.037310e+07 \n",
"9 31.0 SFC2* 6.037320e+07 \n",
"10 47.0 LAC2 6.037111e+07 \n",
"11 269.0 SCUR3 6.037920e+07 \n",
"12 269.0 LCA25* 6.037920e+07 \n",
"13 266.0 SCBP 6.037920e+07 \n",
"14 261.0 PDA1* 6.037910e+07 \n",
"15 261.0 PDA21* 6.037911e+07 \n",
"16 261.0 LCA21* 6.037911e+07 \n",
"17 31.0 LRC3* 6.037901e+07 \n",
"18 260.0 LCM* 6.037900e+07 \n",
"19 261.0 LCA22 6.037910e+07 \n",
"20 31.0 LAC2 6.037235e+07 \n",
"21 31.0 INC2* 6.037601e+07 \n",
"22 31.0 INC1* 6.037601e+07 \n",
"23 31.0 INC2YY 6.037601e+07 \n",
"24 31.0 HAC2YY 6.037602e+07 \n",
"25 261.0 LAR2 6.037276e+07 \n",
"26 246.0 RBR-3 6.037621e+07 \n",
"27 47.0 CCR4* 6.037703e+07 \n",
"28 266.0 LAC2(PV) 6.037276e+07 \n",
"29 261.0 LAR3 6.037272e+07 \n",
"... ... ... ... \n",
"2985187 261.0 NaN 6.037571e+07 \n",
"2985188 261.0 NaN 6.037571e+07 \n",
"2985189 261.0 NaN 6.037571e+07 \n",
"2985190 261.0 NaN 6.037571e+07 \n",
"2985191 261.0 NaN 6.037571e+07 \n",
"2985192 261.0 NaN 6.037571e+07 \n",
"2985193 261.0 NaN 6.037571e+07 \n",
"2985194 261.0 NaN 6.037571e+07 \n",
"2985195 261.0 NaN 6.037571e+07 \n",
"2985196 261.0 NaN 6.037571e+07 \n",
"2985197 261.0 NaN 6.037571e+07 \n",
"2985198 261.0 NaN 6.037571e+07 \n",
"2985199 261.0 NaN 6.037571e+07 \n",
"2985200 261.0 NaN 6.037571e+07 \n",
"2985201 261.0 NaN 6.037571e+07 \n",
"2985202 261.0 NaN 6.037571e+07 \n",
"2985203 261.0 NaN 6.037571e+07 \n",
"2985204 261.0 NaN 6.037571e+07 \n",
"2985205 261.0 NaN 6.037571e+07 \n",
"2985206 261.0 NaN 6.037571e+07 \n",
"2985207 261.0 NaN 6.037571e+07 \n",
"2985208 261.0 NaN 6.037571e+07 \n",
"2985209 261.0 NaN 6.037571e+07 \n",
"2985210 261.0 NaN 6.037571e+07 \n",
"2985211 261.0 NaN 6.037571e+07 \n",
"2985212 261.0 NaN 6.037571e+07 \n",
"2985213 261.0 NaN 6.037571e+07 \n",
"2985214 261.0 NaN 6.037571e+07 \n",
"2985215 261.0 NaN 6.037571e+07 \n",
"2985216 261.0 NaN 6.037571e+07 \n",
"\n",
" regionidcity regionidcounty regionidneighborhood regionidzip \\\n",
"0 37688.0 3101.0 118920.0 96337.0 \n",
"1 37688.0 3101.0 118920.0 96337.0 \n",
"2 51617.0 3101.0 118920.0 96095.0 \n",
"3 12447.0 3101.0 27080.0 96424.0 \n",
"4 12447.0 3101.0 46795.0 96450.0 \n",
"5 12447.0 3101.0 46795.0 96446.0 \n",
"6 12447.0 3101.0 274049.0 96049.0 \n",
"7 396054.0 3101.0 118920.0 96434.0 \n",
"8 396054.0 3101.0 118920.0 96436.0 \n",
"9 47547.0 3101.0 118920.0 96366.0 \n",
"10 12447.0 3101.0 31817.0 96370.0 \n",
"11 25218.0 3101.0 118920.0 96377.0 \n",
"12 25218.0 3101.0 118920.0 96377.0 \n",
"13 54311.0 3101.0 37739.0 96373.0 \n",
"14 40227.0 3101.0 118920.0 97329.0 \n",
"15 40227.0 3101.0 118920.0 97330.0 \n",
"16 40227.0 3101.0 118920.0 97330.0 \n",
"17 5534.0 3101.0 118920.0 97317.0 \n",
"18 5534.0 3101.0 118920.0 97318.0 \n",
"19 40227.0 3101.0 118920.0 97329.0 \n",
"20 12447.0 3101.0 115729.0 96024.0 \n",
"21 45888.0 3101.0 118920.0 96137.0 \n",
"22 45888.0 3101.0 118920.0 96133.0 \n",
"23 45888.0 3101.0 118920.0 96133.0 \n",
"24 45888.0 3101.0 118920.0 96136.0 \n",
"25 12447.0 3101.0 7877.0 96026.0 \n",
"26 33612.0 3101.0 118920.0 96124.0 \n",
"27 51617.0 3101.0 762191.0 96097.0 \n",
"28 12447.0 3101.0 13327.0 96072.0 \n",
"29 12447.0 3101.0 116415.0 96047.0 \n",
"... ... ... ... ... \n",
"2985187 25218.0 3101.0 118920.0 96377.0 \n",
"2985188 25218.0 3101.0 118920.0 96377.0 \n",
"2985189 25218.0 3101.0 118920.0 96377.0 \n",
"2985190 25218.0 3101.0 118920.0 96377.0 \n",
"2985191 25218.0 3101.0 118920.0 96377.0 \n",
"2985192 25218.0 3101.0 118920.0 96377.0 \n",
"2985193 25218.0 3101.0 118920.0 96377.0 \n",
"2985194 25218.0 3101.0 118920.0 96377.0 \n",
"2985195 25218.0 3101.0 118920.0 96377.0 \n",
"2985196 25218.0 3101.0 118920.0 96377.0 \n",
"2985197 25218.0 3101.0 118920.0 96377.0 \n",
"2985198 25218.0 3101.0 118920.0 96377.0 \n",
"2985199 25218.0 3101.0 118920.0 96377.0 \n",
"2985200 25218.0 3101.0 118920.0 96377.0 \n",
"2985201 25218.0 3101.0 118920.0 96377.0 \n",
"2985202 25218.0 3101.0 118920.0 96377.0 \n",
"2985203 25218.0 3101.0 118920.0 96377.0 \n",
"2985204 25218.0 3101.0 118920.0 96377.0 \n",
"2985205 25218.0 3101.0 118920.0 96377.0 \n",
"2985206 25218.0 3101.0 118920.0 96377.0 \n",
"2985207 25218.0 3101.0 118920.0 96377.0 \n",
"2985208 25218.0 3101.0 118920.0 96377.0 \n",
"2985209 25218.0 3101.0 118920.0 96377.0 \n",
"2985210 25218.0 3101.0 118920.0 96377.0 \n",
"2985211 25218.0 3101.0 118920.0 96377.0 \n",
"2985212 25218.0 3101.0 118920.0 96377.0 \n",
"2985213 25218.0 3101.0 118920.0 96377.0 \n",
"2985214 25218.0 3101.0 118920.0 96377.0 \n",
"2985215 25218.0 3101.0 118920.0 96377.0 \n",
"2985216 25218.0 3101.0 118920.0 96377.0 \n",
"\n",
" roomcnt threequarterbathnbr unitcnt yearbuilt numberofstories \\\n",
"0 0.0 1.0 1.0 1963.0 1.0 \n",
"1 0.0 1.0 1.0 1963.0 1.0 \n",
"2 0.0 1.0 2.0 1963.0 1.0 \n",
"3 0.0 1.0 1.0 1948.0 1.0 \n",
"4 0.0 1.0 1.0 1947.0 1.0 \n",
"5 0.0 1.0 1.0 1943.0 1.0 \n",
"6 0.0 1.0 1.0 1963.0 1.0 \n",
"7 0.0 1.0 1.0 1946.0 1.0 \n",
"8 0.0 1.0 1.0 1963.0 1.0 \n",
"9 0.0 1.0 1.0 1978.0 1.0 \n",
"10 0.0 1.0 1.0 1958.0 1.0 \n",
"11 0.0 1.0 1.0 1963.0 1.0 \n",
"12 0.0 1.0 1.0 1963.0 1.0 \n",
"13 0.0 1.0 1.0 1963.0 1.0 \n",
"14 0.0 1.0 1.0 1963.0 1.0 \n",
"15 0.0 1.0 1.0 1963.0 1.0 \n",
"16 0.0 1.0 1.0 1963.0 1.0 \n",
"17 0.0 1.0 1.0 1949.0 1.0 \n",
"18 0.0 1.0 1.0 1956.0 1.0 \n",
"19 0.0 1.0 1.0 2005.0 1.0 \n",
"20 0.0 1.0 1.0 1957.0 1.0 \n",
"21 0.0 1.0 1.0 1963.0 1.0 \n",
"22 0.0 1.0 1.0 1939.0 1.0 \n",
"23 0.0 1.0 1.0 1926.0 1.0 \n",
"24 0.0 1.0 2.0 1938.0 1.0 \n",
"25 0.0 1.0 1.0 1963.0 1.0 \n",
"26 0.0 1.0 2.0 1972.0 1.0 \n",
"27 0.0 1.0 1.0 1955.0 1.0 \n",
"28 0.0 1.0 1.0 2004.0 1.0 \n",
"29 0.0 1.0 1.0 2011.0 1.0 \n",
"... ... ... ... ... ... \n",
"2985187 0.0 1.0 1.0 1963.0 1.0 \n",
"2985188 0.0 1.0 1.0 1963.0 1.0 \n",
"2985189 0.0 1.0 1.0 1963.0 1.0 \n",
"2985190 0.0 1.0 1.0 1963.0 1.0 \n",
"2985191 0.0 1.0 1.0 1963.0 1.0 \n",
"2985192 0.0 1.0 1.0 1963.0 1.0 \n",
"2985193 0.0 1.0 1.0 1963.0 1.0 \n",
"2985194 0.0 1.0 1.0 1963.0 1.0 \n",
"2985195 0.0 1.0 1.0 1963.0 1.0 \n",
"2985196 0.0 1.0 1.0 1963.0 1.0 \n",
"2985197 0.0 1.0 1.0 1963.0 1.0 \n",
"2985198 0.0 1.0 1.0 1963.0 1.0 \n",
"2985199 0.0 1.0 1.0 1963.0 1.0 \n",
"2985200 0.0 1.0 1.0 1963.0 1.0 \n",
"2985201 0.0 1.0 1.0 1963.0 1.0 \n",
"2985202 0.0 1.0 1.0 1963.0 1.0 \n",
"2985203 0.0 1.0 1.0 1963.0 1.0 \n",
"2985204 0.0 1.0 1.0 1963.0 1.0 \n",
"2985205 0.0 1.0 1.0 1963.0 1.0 \n",
"2985206 0.0 1.0 1.0 1963.0 1.0 \n",
"2985207 0.0 1.0 1.0 1963.0 1.0 \n",
"2985208 0.0 1.0 1.0 1963.0 1.0 \n",
"2985209 0.0 1.0 1.0 1963.0 1.0 \n",
"2985210 0.0 1.0 1.0 1963.0 1.0 \n",
"2985211 0.0 1.0 1.0 1963.0 1.0 \n",
"2985212 0.0 1.0 1.0 1963.0 1.0 \n",
"2985213 0.0 1.0 1.0 1963.0 1.0 \n",
"2985214 0.0 1.0 1.0 1963.0 1.0 \n",
"2985215 0.0 1.0 1.0 1963.0 1.0 \n",
"2985216 0.0 1.0 1.0 1963.0 1.0 \n",
"\n",
" structuretaxvaluedollarcnt taxvaluedollarcnt assessmentyear \\\n",
"0 122590.0 9.0 2015.0 \n",
"1 122590.0 27516.0 2015.0 \n",
"2 650756.0 1413387.0 2015.0 \n",
"3 571346.0 1156834.0 2015.0 \n",
"4 193796.0 433491.0 2015.0 \n",
"5 176383.0 283315.0 2015.0 \n",
"6 397945.0 554573.0 2015.0 \n",
"7 101998.0 688486.0 2015.0 \n",
"8 122590.0 9.0 2015.0 \n",
"9 218440.0 261201.0 2015.0 \n",
"10 245834.0 430208.0 2015.0 \n",
"11 122590.0 9.0 2015.0 \n",
"12 122590.0 171200.0 2015.0 \n",
"13 122590.0 4265.0 2015.0 \n",
"14 122590.0 10.0 2015.0 \n",
"15 122590.0 10.0 2015.0 \n",
"16 122590.0 2077.0 2015.0 \n",
"17 32654.0 62424.0 2015.0 \n",
"18 56736.0 102385.0 2015.0 \n",
"19 218982.0 291973.0 2015.0 \n",
"20 197599.0 503752.0 2015.0 \n",
"21 35876.0 49928.0 2015.0 \n",
"22 69879.0 231720.0 2015.0 \n",
"23 41917.0 181667.0 2015.0 \n",
"24 44959.0 133717.0 2015.0 \n",
"25 122590.0 124.0 2015.0 \n",
"26 267623.0 818739.0 2015.0 \n",
"27 204800.0 786584.0 2015.0 \n",
"28 229399.0 352198.0 2015.0 \n",
"29 334432.0 835036.0 2015.0 \n",
"... ... ... ... \n",
"2985187 122590.0 306086.0 2015.0 \n",
"2985188 122590.0 306086.0 2015.0 \n",
"2985189 122590.0 306086.0 2015.0 \n",
"2985190 122590.0 306086.0 2015.0 \n",
"2985191 122590.0 306086.0 2015.0 \n",
"2985192 122590.0 306086.0 2015.0 \n",
"2985193 122590.0 306086.0 2015.0 \n",
"2985194 122590.0 306086.0 2015.0 \n",
"2985195 122590.0 306086.0 2015.0 \n",
"2985196 122590.0 306086.0 2015.0 \n",
"2985197 122590.0 306086.0 2015.0 \n",
"2985198 122590.0 306086.0 2015.0 \n",
"2985199 122590.0 306086.0 2015.0 \n",
"2985200 122590.0 306086.0 2015.0 \n",
"2985201 122590.0 306086.0 2015.0 \n",
"2985202 122590.0 306086.0 2015.0 \n",
"2985203 122590.0 306086.0 2015.0 \n",
"2985204 122590.0 306086.0 2015.0 \n",
"2985205 122590.0 306086.0 2015.0 \n",
"2985206 122590.0 306086.0 2015.0 \n",
"2985207 122590.0 306086.0 2015.0 \n",
"2985208 122590.0 306086.0 2015.0 \n",
"2985209 122590.0 306086.0 2015.0 \n",
"2985210 122590.0 306086.0 2015.0 \n",
"2985211 122590.0 306086.0 2015.0 \n",
"2985212 122590.0 306086.0 2015.0 \n",
"2985213 122590.0 306086.0 2015.0 \n",
"2985214 122590.0 306086.0 2015.0 \n",
"2985215 122590.0 306086.0 2015.0 \n",
"2985216 122590.0 306086.0 2015.0 \n",
"\n",
" landtaxvaluedollarcnt taxamount censustractandblock \n",
"0 9.0 3991.78 6.037572e+13 \n",
"1 27516.0 3991.78 6.037572e+13 \n",
"2 762631.0 20800.37 6.037572e+13 \n",
"3 585488.0 14557.57 6.037572e+13 \n",
"4 239695.0 5725.17 6.037572e+13 \n",
"5 106932.0 3661.28 6.037572e+13 \n",
"6 156628.0 6773.34 6.037572e+13 \n",
"7 586488.0 7857.84 6.037572e+13 \n",
"8 9.0 3991.78 6.037572e+13 \n",
"9 42761.0 4054.76 6.037572e+13 \n",
"10 184374.0 6014.18 6.037572e+13 \n",
"11 9.0 3991.78 6.037572e+13 \n",
"12 171200.0 4690.68 6.037572e+13 \n",
"13 4265.0 3991.78 6.037572e+13 \n",
"14 10.0 3991.78 6.037572e+13 \n",
"15 10.0 3991.78 6.037572e+13 \n",
"16 2077.0 174.21 6.037572e+13 \n",
"17 29770.0 2330.24 6.037572e+13 \n",
"18 45649.0 4162.56 6.037572e+13 \n",
"19 72991.0 6941.39 6.037572e+13 \n",
"20 306153.0 6840.34 6.037572e+13 \n",
"21 14052.0 1522.08 6.037572e+13 \n",
"22 161841.0 3703.54 6.037572e+13 \n",
"23 139750.0 2992.02 6.037572e+13 \n",
"24 88758.0 2797.70 6.037572e+13 \n",
"25 124.0 3991.78 6.037572e+13 \n",
"26 551116.0 10455.41 6.037572e+13 \n",
"27 581784.0 11304.81 6.037572e+13 \n",
"28 122799.0 6165.36 6.037572e+13 \n",
"29 500604.0 10244.94 6.037572e+13 \n",
"... ... ... ... \n",
"2985187 167042.0 3991.78 6.037572e+13 \n",
"2985188 167042.0 3991.78 6.037572e+13 \n",
"2985189 167042.0 3991.78 6.037572e+13 \n",
"2985190 167042.0 3991.78 6.037572e+13 \n",
"2985191 167042.0 3991.78 6.037572e+13 \n",
"2985192 167042.0 3991.78 6.037572e+13 \n",
"2985193 167042.0 3991.78 6.037572e+13 \n",
"2985194 167042.0 3991.78 6.037572e+13 \n",
"2985195 167042.0 3991.78 6.037572e+13 \n",
"2985196 167042.0 3991.78 6.037572e+13 \n",
"2985197 167042.0 3991.78 6.037572e+13 \n",
"2985198 167042.0 3991.78 6.037572e+13 \n",
"2985199 167042.0 3991.78 6.037572e+13 \n",
"2985200 167042.0 3991.78 6.037572e+13 \n",
"2985201 167042.0 3991.78 6.037572e+13 \n",
"2985202 167042.0 3991.78 6.037572e+13 \n",
"2985203 167042.0 3991.78 6.037572e+13 \n",
"2985204 167042.0 3991.78 6.037572e+13 \n",
"2985205 167042.0 3991.78 6.037572e+13 \n",
"2985206 167042.0 3991.78 6.037572e+13 \n",
"2985207 167042.0 3991.78 6.037572e+13 \n",
"2985208 167042.0 3991.78 6.037572e+13 \n",
"2985209 167042.0 3991.78 6.037572e+13 \n",
"2985210 167042.0 3991.78 6.037572e+13 \n",
"2985211 167042.0 3991.78 6.037572e+13 \n",
"2985212 167042.0 3991.78 6.037572e+13 \n",
"2985213 167042.0 3991.78 6.037572e+13 \n",
"2985214 167042.0 3991.78 6.037572e+13 \n",
"2985215 167042.0 3991.78 6.037572e+13 \n",
"2985216 167042.0 3991.78 6.037572e+13 \n",
"\n",
"[2985217 rows x 38 columns]"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"prop.fillna(prop.median(),inplace=True)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"_cell_guid": "92b38329-abab-4f80-ad3c-e51180980afc",
"_uuid": "e60a58c6767121015e76ce2c0bb655cf046a6851",
"collapsed": true
},
"outputs": [],
"source": [
"prop.drop(['propertyzoningdesc','propertycountylandusecode'], axis=1, inplace=True)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"_cell_guid": "416a5cfa-bce4-411c-939b-7783c2b84af3",
"_uuid": "ff22dafb640486ee27da95dd80e7ad1511f7124f"
},
"outputs": [
{
"data": {
"text/plain": [
"Index([], dtype='object')"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"prop.select_dtypes(include=[\"object\"]).columns"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"_cell_guid": "e2a567fa-d021-4738-9a37-da8e869114f6",
"_uuid": "0b449f3f272b2363c83dd843d29e8511e2314f63",
"collapsed": true
},
"outputs": [],
"source": [
"cat_var_dict = {'airconditioningdesc':10,'heatingorsystemdesc':10,'propertylandusedesc':10,\n",
" 'storydesc':2,'architecturalstyledesc':10,'typeconstructiondesc':10}"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"_cell_guid": "78b1a7b4-5847-4897-9fe1-24c52aa242e4",
"_uuid": "ac40e28162300c7bcf866b052146a38436d2c77b",
"collapsed": true
},
"outputs": [],
"source": [
"cat_vars = [o[0] for o in \n",
" sorted(cat_var_dict.items(), key=operator.itemgetter(1), reverse=True)]"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"_cell_guid": "149b75fe-3101-46b8-bf8e-c6beebd653c7",
"_uuid": "ef233ff3bf1aac2b52aff274b6fb8133a9a9faca",
"collapsed": true
},
"outputs": [],
"source": [
"contin_vars = prop.select_dtypes(include=['float64']).columns"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"_cell_guid": "12dd984e-b1aa-4aab-8a24-a0b522b79c88",
"_uuid": "91d1d2203c3d12847ac02c20473342465940e50d",
"collapsed": true
},
"outputs": [],
"source": [
"cat_maps = [(o, LabelEncoder()) for o in cat_vars]\n",
"contin_maps = [([o], StandardScaler()) for o in contin_vars]"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"_cell_guid": "e1cee25d-6830-4fa3-8a27-e990ae6fd5a0",
"_uuid": "67b7c75942eaccb3160b82f7817eb8eff1f73256",
"collapsed": true
},
"outputs": [
{
"ename": "KeyError",
"evalue": "'airconditioningdesc'",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m 2392\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2393\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2394\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc (pandas/_libs/index.c:5239)\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc (pandas/_libs/index.c:5085)\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item (pandas/_libs/hashtable.c:20405)\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item (pandas/_libs/hashtable.c:20359)\u001b[0;34m()\u001b[0m\n",
"\u001b[0;31mKeyError\u001b[0m: 'airconditioningdesc'",
"\nDuring handling of the above exception, another exception occurred:\n",
"\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-17-9be2eb403944>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0mcat_mapper\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mDataFrameMapper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcat_maps\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mcat_map_fit\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcat_mapper\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprop\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3\u001b[0m \u001b[0mcat_cols\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcat_map_fit\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfeatures\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/sklearn_pandas/dataframe_mapper.py\u001b[0m in \u001b[0;36mfit\u001b[0;34m(self, X, y)\u001b[0m\n\u001b[1;32m 194\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mtransformers\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 195\u001b[0m _call_fit(transformers.fit,\n\u001b[0;32m--> 196\u001b[0;31m self._get_col_subset(X, columns, input_df), y)\n\u001b[0m\u001b[1;32m 197\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 198\u001b[0m \u001b[0;31m# handle features not explicitly selected\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/sklearn_pandas/dataframe_mapper.py\u001b[0m in \u001b[0;36m_get_col_subset\u001b[0;34m(self, X, cols, input_df)\u001b[0m\n\u001b[1;32m 157\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 158\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mreturn_vector\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 159\u001b[0;31m \u001b[0mt\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mX\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mcols\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 160\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 161\u001b[0m \u001b[0mt\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mX\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mcols\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 2060\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_multilevel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2061\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2062\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_column\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2063\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2064\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_getitem_column\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m_getitem_column\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 2067\u001b[0m \u001b[0;31m# get column\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2068\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_unique\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2069\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_item_cache\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2070\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2071\u001b[0m \u001b[0;31m# duplicate columns & possible reduce dimensionality\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36m_get_item_cache\u001b[0;34m(self, item)\u001b[0m\n\u001b[1;32m 1532\u001b[0m \u001b[0mres\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcache\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1533\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mres\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1534\u001b[0;31m \u001b[0mvalues\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_data\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1535\u001b[0m \u001b[0mres\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_box_item_values\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalues\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1536\u001b[0m \u001b[0mcache\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mres\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/internals.py\u001b[0m in \u001b[0;36mget\u001b[0;34m(self, item, fastpath)\u001b[0m\n\u001b[1;32m 3588\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3589\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0misnull\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3590\u001b[0;31m \u001b[0mloc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3591\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3592\u001b[0m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0misnull\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m 2393\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2394\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2395\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_maybe_cast_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2396\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2397\u001b[0m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtolerance\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtolerance\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc (pandas/_libs/index.c:5239)\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc (pandas/_libs/index.c:5085)\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item (pandas/_libs/hashtable.c:20405)\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item (pandas/_libs/hashtable.c:20359)\u001b[0;34m()\u001b[0m\n",
"\u001b[0;31mKeyError\u001b[0m: 'airconditioningdesc'"
]
}
],
"source": [
"cat_mapper = DataFrameMapper(cat_maps)\n",
"cat_map_fit = cat_mapper.fit(prop)\n",
"cat_cols = len(cat_map_fit.features)\n"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"_cell_guid": "2d4f7a86-f411-4ed4-b13f-0dc17fe94316",
"_uuid": "0759bc8ef7c348057356fe277b32a44d89980ad3",
"collapsed": true
},
"outputs": [],
"source": [
"contin_mapper = DataFrameMapper(contin_maps)\n",
"contin_map_fit = contin_mapper.fit(prop)\n",
"contin_cols = len(contin_map_fit.features)\n"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"_cell_guid": "93c6a0ee-7af5-4d5e-bb48-2c751cb208c9",
"_uuid": "44180d72238fb0c7a063b444c242c70616c4594d"
},
"outputs": [
{
"ename": "NameError",
"evalue": "name 'cat_map_fit' is not defined",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-19-ea12268f4e63>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mcat_map_fit\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtransform\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprop\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcontin_map_fit\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtransform\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprop\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;31mNameError\u001b[0m: name 'cat_map_fit' is not defined"
]
}
],
"source": [
"cat_map_fit.transform(prop)[0,:5], contin_map_fit.transform(prop)[0,:5]"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"_cell_guid": "3db3c2da-fefc-4134-b626-1460948cf52f",
"_uuid": "4b671deab3d39ec5b51b244dd9dd4d37bf84763b",
"collapsed": true
},
"outputs": [],
"source": [
"# print('Creating training set ...')\n",
"\n",
"df_train = train.merge(prop, how='left', on='parcelid')"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"_cell_guid": "9cf8b201-a32c-46c0-9fb5-40659220b8c2",
"_uuid": "7f2a0a1ddc48f2fc1ebd7764bfed45e5e2d81cfb",
"collapsed": true
},
"outputs": [],
"source": [
"# print('Creating test set ...')\n",
"\n",
"sample['parcelid'] = sample['ParcelId']\n",
"df_test = sample.merge(prop, on='parcelid', how='left')\n"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"_cell_guid": "69812fe2-0fd8-4cbb-9186-8c0d6c250536",
"_uuid": "5dc6674c399fddaa6a60dffb2d19aae79d8a09e8",
"collapsed": true
},
"outputs": [],
"source": [
"def missmatch_col():\n",
" extra_train_cols = []\n",
" extra_test_cols = []\n",
"\n",
" for i in df_train.columns:\n",
" if i in df_test.columns:\n",
" continue\n",
" else:\n",
" extra_train_cols.append(i)\n",
"\n",
" for i in df_test.columns:\n",
" if i in df_train.columns:\n",
" continue\n",
" else:\n",
" extra_test_cols.append(i)\n",
" print(\"Extra Columns in Train, \",\"Extra columns in Test\") \n",
" return extra_train_cols,extra_test_cols"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {
"_cell_guid": "9f6099e5-7b53-4463-8d7a-55435e84a475",
"_uuid": "018d97f5ff111f79203e6a4e25368a39a139ee1b",
"collapsed": true
},
"outputs": [],
"source": [
"def add_datepart(df):\n",
" df.transactiondate = pd.to_datetime(df.transactiondate)\n",
" df[\"Year\"] = df.transactiondate.dt.year\n",
" df[\"Month\"] = df.transactiondate.dt.month\n",
" df[\"Week\"] = df.transactiondate.dt.week\n",
" df[\"Day\"] = df.transactiondate.dt.day"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {
"_cell_guid": "fce803fb-91b9-4edf-a359-aca3c7ad6ba4",
"_uuid": "d2705ef6445ab2461c63ced38a4867620b0a366d",
"collapsed": true
},
"outputs": [],
"source": [
"y_train = df_train['logerror'].values"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {
"_cell_guid": "57c6f17c-c48f-4d11-9fcb-f0b2fceb1d4d",
"_uuid": "7f6b7a5f1f44fcb1b119ab320d5fd153c9dca8d2"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Extra Columns in Train, Extra columns in Test\n",
"Extra Columns in Train, Extra columns in Test\n"
]
}
],
"source": [
"df_train.drop(missmatch_col()[0], axis=1, inplace=True)\n",
"df_test.drop(missmatch_col()[1], axis=1, inplace=True)"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {
"_cell_guid": "2454cdbf-df81-4a8d-bb22-cad75fb83025",
"_uuid": "7667478a0aee15f097a7ed6424af9ca4f6afa504",
"collapsed": true
},
"outputs": [],
"source": [
"df_test.drop(['parcelid'], axis=1, inplace=True)\n",
"df_train.drop(['parcelid'], axis=1, inplace=True)"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {
"_cell_guid": "1c986f04-91a7-4e73-a87d-2cd19f5e99a5",
"_uuid": "5d0e7bb05f8b471f0e3efa27537381e100c6a944",
"collapsed": true
},
"outputs": [],
"source": [
"def cat_preproc(dat):\n",
" return cat_map_fit.transform(dat).astype(np.int64)"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {
"_cell_guid": "d6b398ad-d61c-4288-aff4-ea61f56d113a",
"_uuid": "35fd7d26217f65485753e65442415a8214582f13",
"collapsed": true
},
"outputs": [],
"source": [
"def contin_preproc(dat):\n",
" return contin_map_fit.transform(dat).astype(np.float32)"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {
"_cell_guid": "fdec060a-8351-45c3-9e2f-634d5aaad7a1",
"_uuid": "4a7dfd3c0a36f2b92c6017349b98ae6754cfeb22",
"collapsed": true
},
"outputs": [],
"source": [
"split = 80000\n",
"x_train, y_train, x_valid, y_valid = df_train[:split], y_train[:split], df_train[split:], y_train[split:]"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {
"_cell_guid": "df0dacae-86fc-4325-8137-90c749762ae0",
"_uuid": "f639ce3f36e6dafc93030268294d9ee0b522a126",
"collapsed": true
},
"outputs": [
{
"ename": "NameError",
"evalue": "name 'cat_map_fit' is not defined",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-30-e6a8472ee224>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mcat_map_train\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcat_preproc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx_train\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mcat_map_valid\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcat_preproc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx_valid\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m<ipython-input-27-41f1760cbee2>\u001b[0m in \u001b[0;36mcat_preproc\u001b[0;34m(dat)\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mcat_preproc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdat\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mcat_map_fit\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtransform\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdat\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mastype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mint64\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;31mNameError\u001b[0m: name 'cat_map_fit' is not defined"
]
}
],
"source": [
"cat_map_train = cat_preproc(x_train)\n",
"cat_map_valid = cat_preproc(x_valid)"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {
"_cell_guid": "b247c0ac-21af-45b7-b2c0-7d5bfc62c724",
"_uuid": "3b3d304cbacc3a385272382e3e81e9bd80d0d5f2",
"collapsed": true
},
"outputs": [],
"source": [
"contin_map_train = contin_preproc(x_train)\n",
"contin_map_valid = contin_preproc(x_valid)"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {
"_cell_guid": "a883b1b2-9da3-42ab-8593-d92e8b6d1b10",
"_uuid": "604062bd3db85dea93bb9eb7d63be59dd768a040",
"collapsed": true
},
"outputs": [
{
"ename": "NameError",
"evalue": "name 'cat_map_fit' is not defined",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-32-71b68dbdc6b7>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mcat_map_test\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcat_preproc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf_test\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mcontin_map_test\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcontin_preproc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf_test\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m<ipython-input-27-41f1760cbee2>\u001b[0m in \u001b[0;36mcat_preproc\u001b[0;34m(dat)\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mcat_preproc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdat\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mcat_map_fit\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtransform\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdat\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mastype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mint64\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;31mNameError\u001b[0m: name 'cat_map_fit' is not defined"
]
}
],
"source": [
"cat_map_test = cat_preproc(df_test)\n",
"contin_map_test = contin_preproc(df_test)"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {
"_cell_guid": "378ec37d-fd50-4c84-a2d7-b08ae5907cb3",
"_uuid": "b11755b43c8f17ac26810a88880ad2991446c678",
"collapsed": true
},
"outputs": [],
"source": [
"def split_cols(arr): return np.hsplit(arr,arr.shape[1])"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {
"_cell_guid": "e0df7cd9-e4c8-4160-a77d-4e6504b21c34",
"_uuid": "868bd49edbb19032b99192beae5f527c738455fb",
"collapsed": true
},
"outputs": [
{
"ename": "NameError",
"evalue": "name 'cat_map_train' is not defined",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-34-8ece30e3826a>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mmap_train\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msplit_cols\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcat_map_train\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mcontin_map_train\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mmap_valid\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msplit_cols\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcat_map_valid\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mcontin_map_valid\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mNameError\u001b[0m: name 'cat_map_train' is not defined"
]
}
],
"source": [
"map_train = split_cols(cat_map_train) + [contin_map_train]\n",
"map_valid = split_cols(cat_map_valid) + [contin_map_valid]"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {
"_cell_guid": "5b94973c-7ca7-458c-9416-6d1ff29aec59",
"_uuid": "5d3ce6dfa28b739a7c1e400055ea013b122cce15",
"collapsed": true
},
"outputs": [
{
"ename": "NameError",
"evalue": "name 'cat_map_test' is not defined",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-35-c4b689e08e07>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mmap_test\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msplit_cols\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcat_map_test\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mcontin_map_test\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;31mNameError\u001b[0m: name 'cat_map_test' is not defined"
]
}
],
"source": [
"map_test = split_cols(cat_map_test) + [contin_map_test]"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {
"_cell_guid": "bd628486-e50a-4f0d-8fa9-149c9ac77855",
"_uuid": "bcf9a388d909041ec6ee51510f5b57c41bc9298b",
"collapsed": true
},
"outputs": [],
"source": [
"def cat_map_info(feat): return feat[0], len(feat[1].classes_)"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {
"_cell_guid": "ced7d817-9278-4e20-85e5-dc6a8323a46e",
"_uuid": "3ad65cb223c36e30bdee349cdbbae98ac38e170d",
"collapsed": true
},
"outputs": [],
"source": [
"def emb_init(shape, dtype=None):\n",
" return K.random_normal(shape, dtype=dtype)"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {
"_cell_guid": "73cf70a8-c916-4b24-929a-dc6c15474038",
"_uuid": "4f86bf72d96bb8d84a30faab747e2666b85ccb2b",
"collapsed": true
},
"outputs": [],
"source": [
"def get_emb(feat):\n",
" name, c = cat_map_info(feat)\n",
" c2 = (c+1)//2\n",
" inp = Input((1,), dtype='int64', name=name+'_in')\n",
" # , W_regularizer=l2(1e-6)\n",
" u = Flatten(name=name+'_flt')(Embedding(c, c2, input_length=1, init=emb_init)(inp))\n",
"# u = Flatten(name=name+'_flt')(Embedding(c, c2, input_length=1)(inp))\n",
" return inp,u"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {
"_cell_guid": "e7db6a3d-e101-45a9-bf0d-fdb4ace9f46e",
"_uuid": "9a20e050a4659ca1846a017f4455e5c8f738d8fb",
"collapsed": true
},
"outputs": [],
"source": [
"def get_contin(feat):\n",
" name = feat[0][0]\n",
" inp = Input((1,), name=name+'_in')\n",
" return inp, Dense(1, name=name+'_d', init=my_init(1.))(inp)"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {
"_cell_guid": "9f5bd678-bf93-4a66-a4af-a783f924b19e",
"_uuid": "431c90a7247dd8d61de710614e4cc554597265f2",
"collapsed": true
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_inspect.py:45: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() or inspect.getfullargspec()\n",
" if d.decorator_argspec is not None), _inspect.getargspec(target))\n"
]
}
],
"source": [
"contin_inp = Input((contin_cols,), name='contin')\n",
"contin_out = Dense(contin_cols*10, activation='relu', name='contin_d')(contin_inp)\n",
"contin_out = BatchNormalization()(contin_out)"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {
"_cell_guid": "33ad7c35-4051-4c71-8495-b8c8a03a7066",
"_uuid": "cb5e768d9c2ef1377cc6cce18dfd68e923fb94e4"
},
"outputs": [
{
"ename": "NameError",
"evalue": "name 'cat_map_fit' is not defined",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-41-b67b5cbe8a78>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0membs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mget_emb\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfeat\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mfeat\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mcat_map_fit\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfeatures\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmerge\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0memb\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0minp\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0memb\u001b[0m \u001b[0;32min\u001b[0m \u001b[0membs\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mcontin_out\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmode\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'concat'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0mx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mDense\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m500\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mactivation\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'relu'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkernel_initializer\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'uniform'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0mx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mDense\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m200\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mactivation\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'relu'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkernel_initializer\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'uniform'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mDropout\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0.2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mNameError\u001b[0m: name 'cat_map_fit' is not defined"
]
}
],
"source": [
"embs = [get_emb(feat) for feat in cat_map_fit.features]\n",
"x = merge([emb for inp,emb in embs] + [contin_out], mode='concat')\n",
"x = Dense(500, activation='relu', kernel_initializer='uniform')(x)\n",
"x = Dense(200, activation='relu', kernel_initializer='uniform')(x)\n",
"x = Dropout(0.2)(x)\n",
"x = Dense(1, activation='linear')(x)\n",
"\n",
"model = Model([inp for inp,emb in embs] + [contin_inp], x)\n",
"model.compile('adam', 'mean_absolute_error')"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {
"_cell_guid": "ff368e93-5b5c-47d8-8140-37e1f509526c",
"_uuid": "407d790c2f85bafc07f116adbc7f1263753fec1a"
},
"outputs": [
{
"ename": "NameError",
"evalue": "name 'model' is not defined",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-42-8d74a1e715f9>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m histMax = model.fit(map_train, y_train, batch_size=64, epochs=5,\n\u001b[0m\u001b[1;32m 2\u001b[0m verbose=0, validation_data=(map_valid, y_valid))\n",
"\u001b[0;31mNameError\u001b[0m: name 'model' is not defined"
]
}
],
"source": [
"histMax = model.fit(map_train, y_train, batch_size=64, epochs=5,\n",
" verbose=0, validation_data=(map_valid, y_valid))"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {
"_cell_guid": "4c589737-1534-4ae2-9678-a91505b5cdd3",
"_uuid": "1af9347acd6c25016f7a6fbbbd57f42631259fa2",
"collapsed": true
},
"outputs": [
{
"ename": "NameError",
"evalue": "name 'model' is not defined",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-43-16326c570cea>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mans\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msqueeze\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpredict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmap_test\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;31mNameError\u001b[0m: name 'model' is not defined"
]
}
],
"source": [
"ans = np.squeeze(model.predict(map_test))"
]
},
{
"cell_type": "code",
"execution_count": 44,
"metadata": {
"_cell_guid": "a2779801-1be2-4490-ad32-28cff2a2e98b",
"_uuid": "81d5c3fcc787194ded5910b84ba098ba27f3675e"
},
"outputs": [
{
"ename": "FileNotFoundError",
"evalue": "File b'sample_submission.csv' does not exist",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-44-184691a744f6>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0msample\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'sample_submission.csv'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mc\u001b[0m \u001b[0;32min\u001b[0m \u001b[0msample\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0msample\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;34m'ParcelId'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0msample\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mc\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mans\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Writing csv ...'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36mparser_f\u001b[0;34m(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, escapechar, comment, encoding, dialect, tupleize_cols, error_bad_lines, warn_bad_lines, skipfooter, skip_footer, doublequote, delim_whitespace, as_recarray, compact_ints, use_unsigned, low_memory, buffer_lines, memory_map, float_precision)\u001b[0m\n\u001b[1;32m 653\u001b[0m skip_blank_lines=skip_blank_lines)\n\u001b[1;32m 654\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 655\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0m_read\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 656\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 657\u001b[0m \u001b[0mparser_f\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__name__\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m_read\u001b[0;34m(filepath_or_buffer, kwds)\u001b[0m\n\u001b[1;32m 403\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 404\u001b[0m \u001b[0;31m# Create the parser.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 405\u001b[0;31m \u001b[0mparser\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mTextFileReader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 406\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 407\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mchunksize\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0miterator\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, f, engine, **kwds)\u001b[0m\n\u001b[1;32m 760\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'has_index_names'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'has_index_names'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 761\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 762\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_make_engine\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mengine\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 763\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 764\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mclose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m_make_engine\u001b[0;34m(self, engine)\u001b[0m\n\u001b[1;32m 964\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_make_engine\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mengine\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'c'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 965\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mengine\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'c'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 966\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mCParserWrapper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 967\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 968\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mengine\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'python'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, src, **kwds)\u001b[0m\n\u001b[1;32m 1580\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'allow_leading_cols'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex_col\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1581\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1582\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_reader\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mparsers\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTextReader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msrc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1583\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1584\u001b[0m \u001b[0;31m# XXX\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader.__cinit__ (pandas/_libs/parsers.c:4209)\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader._setup_parser_source (pandas/_libs/parsers.c:8873)\u001b[0;34m()\u001b[0m\n",
"\u001b[0;31mFileNotFoundError\u001b[0m: File b'sample_submission.csv' does not exist"
]
}
],
"source": [
"sample = pd.read_csv('sample_submission.csv')\n",
"for c in sample.columns[sample.columns != 'ParcelId']:\n",
" sample[c] = ans\n",
"\n",
"print('Writing csv ...')\n",
"sample.to_csv('emb_model.csv', index=False, float_format='%.4f')"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.1"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
| 0001/480/1480037.ipynb | s3://data-agents/kaggle-outputs/sharded/034_00001.jsonl.gz |
{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "f3cf36f4-1d47-439f-b228-a75dc22428e1",
"_uuid": "a26014c0756c4964275554d6e25d394acc6ea94f"
},
"source": []
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "86814dd3-4fde-40ca-9fb2-217692640c96",
"_uuid": "6e0e20bb4ace9b58239faa3e6ba50a1a0f286247"
},
"source": [
"**STATISCAL ANALYSIS**"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"_cell_guid": "a9937524-7b12-4d77-aef2-98db51288d24",
"_uuid": "47e2a9dc3fd45ff4a5a3c40fb3b6fcce765f8546",
"collapsed": true
},
"outputs": [],
"source": [
"import numpy\n",
"import pandas\n",
"from sklearn.feature_selection import RFE\n",
"from sklearn.ensemble import ExtraTreesRegressor\n",
"\n",
"\n",
"import matplotlib.pyplot as plt\n",
"from pandas.tools.plotting import scatter_matrix\n",
"\n",
"\n",
"# fix random seed for reproducibility\n",
"seed = 7\n",
"numpy.random.seed(seed)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"_cell_guid": "d481f275-7b6c-4f1b-a16f-eaab2b5ffba6",
"_uuid": "3f54f23093078816fe0c8377a18d09c48fd48a02",
"collapsed": true
},
"outputs": [],
"source": [
"# load dataset\n",
"dataframe = pandas.read_csv(r\"../input/concrete_data.csv\")"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"_cell_guid": "87b2d6c2-cfa3-4986-a3d6-3a59e98e0f54",
"_uuid": "560db596a1195e33fb53526fd15cbce38075097b"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Head: cement blast_furnace_slag fly_ash water superplasticizer \\\n",
"0 540.0 0.0 0.0 162.0 2.5 \n",
"1 540.0 0.0 0.0 162.0 2.5 \n",
"2 332.5 142.5 0.0 228.0 0.0 \n",
"3 332.5 142.5 0.0 228.0 0.0 \n",
"4 198.6 132.4 0.0 192.0 0.0 \n",
"\n",
" coarse_aggregate fine_aggregate age concrete_compressive_strength \n",
"0 1040.0 676.0 28 79.99 \n",
"1 1055.0 676.0 28 61.89 \n",
"2 932.0 594.0 270 40.27 \n",
"3 932.0 594.0 365 41.05 \n",
"4 978.4 825.5 360 44.30 \n"
]
}
],
"source": [
"print(\"Head:\", dataframe.head())"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"_cell_guid": "a271717d-52f2-45e4-8cf9-38b95af9c83e",
"_uuid": "9da974c494fea5536c22abf67ff44956df2815e2"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Statistical Description: cement blast_furnace_slag fly_ash water \\\n",
"count 1030.000000 1030.000000 1030.000000 1030.000000 \n",
"mean 281.167864 73.895825 54.188350 181.567282 \n",
"std 104.506364 86.279342 63.997004 21.354219 \n",
"min 102.000000 0.000000 0.000000 121.800000 \n",
"25% 192.375000 0.000000 0.000000 164.900000 \n",
"50% 272.900000 22.000000 0.000000 185.000000 \n",
"75% 350.000000 142.950000 118.300000 192.000000 \n",
"max 540.000000 359.400000 200.100000 247.000000 \n",
"\n",
" superplasticizer coarse_aggregate fine_aggregate age \\\n",
"count 1030.000000 1030.000000 1030.000000 1030.000000 \n",
"mean 6.204660 972.918932 773.580485 45.662136 \n",
"std 5.973841 77.753954 80.175980 63.169912 \n",
"min 0.000000 801.000000 594.000000 1.000000 \n",
"25% 0.000000 932.000000 730.950000 7.000000 \n",
"50% 6.400000 968.000000 779.500000 28.000000 \n",
"75% 10.200000 1029.400000 824.000000 56.000000 \n",
"max 32.200000 1145.000000 992.600000 365.000000 \n",
"\n",
" concrete_compressive_strength \n",
"count 1030.000000 \n",
"mean 35.817961 \n",
"std 16.705742 \n",
"min 2.330000 \n",
"25% 23.710000 \n",
"50% 34.445000 \n",
"75% 46.135000 \n",
"max 82.600000 \n"
]
}
],
"source": [
"\n",
"\n",
"print(\"Statistical Description:\", dataframe.describe())"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"_cell_guid": "e8ccf9e1-6bc2-4587-a5d4-29b03ddb490d",
"_uuid": "ebe7a09494816f1193f5f4b06ec2bf4a9a594a42"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Shape: (1030, 9)\n"
]
}
],
"source": [
"print(\"Shape:\", dataframe.shape)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"_cell_guid": "3aa5d0d2-7b30-426f-b088-fdc86d750647",
"_uuid": "7a17db9cfb382218a133135f1502d6826b92e046"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Data Types: cement float64\n",
"blast_furnace_slag float64\n",
"fly_ash float64\n",
"water float64\n",
"superplasticizer float64\n",
"coarse_aggregate float64\n",
"fine_aggregate float64\n",
"age int64\n",
"concrete_compressive_strength float64\n",
"dtype: object\n"
]
}
],
"source": [
"print(\"Data Types:\", dataframe.dtypes)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"_cell_guid": "d6a53e9b-b896-4249-a81e-22c32c889913",
"_uuid": "f3931726fbe843d4922bd607bb64b08e70342f2e"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Correlation: cement blast_furnace_slag fly_ash \\\n",
"cement 1.000000 -0.275216 -0.397467 \n",
"blast_furnace_slag -0.275216 1.000000 -0.323580 \n",
"fly_ash -0.397467 -0.323580 1.000000 \n",
"water -0.081587 0.107252 -0.256984 \n",
"superplasticizer 0.092386 0.043270 0.377503 \n",
"coarse_aggregate -0.109349 -0.283999 -0.009961 \n",
"fine_aggregate -0.222718 -0.281603 0.079108 \n",
"age 0.081946 -0.044246 -0.154371 \n",
"concrete_compressive_strength 0.497832 0.134829 -0.105755 \n",
"\n",
" water superplasticizer coarse_aggregate \\\n",
"cement -0.081587 0.092386 -0.109349 \n",
"blast_furnace_slag 0.107252 0.043270 -0.283999 \n",
"fly_ash -0.256984 0.377503 -0.009961 \n",
"water 1.000000 -0.657533 -0.182294 \n",
"superplasticizer -0.657533 1.000000 -0.265999 \n",
"coarse_aggregate -0.182294 -0.265999 1.000000 \n",
"fine_aggregate -0.450661 0.222691 -0.178481 \n",
"age 0.277618 -0.192700 -0.003016 \n",
"concrete_compressive_strength -0.289633 0.366079 -0.164935 \n",
"\n",
" fine_aggregate age \\\n",
"cement -0.222718 0.081946 \n",
"blast_furnace_slag -0.281603 -0.044246 \n",
"fly_ash 0.079108 -0.154371 \n",
"water -0.450661 0.277618 \n",
"superplasticizer 0.222691 -0.192700 \n",
"coarse_aggregate -0.178481 -0.003016 \n",
"fine_aggregate 1.000000 -0.156095 \n",
"age -0.156095 1.000000 \n",
"concrete_compressive_strength -0.167241 0.328873 \n",
"\n",
" concrete_compressive_strength \n",
"cement 0.497832 \n",
"blast_furnace_slag 0.134829 \n",
"fly_ash -0.105755 \n",
"water -0.289633 \n",
"superplasticizer 0.366079 \n",
"coarse_aggregate -0.164935 \n",
"fine_aggregate -0.167241 \n",
"age 0.328873 \n",
"concrete_compressive_strength 1.000000 \n"
]
}
],
"source": [
"print(\"Correlation:\", dataframe.corr(method='pearson'))"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "4578f561-3a5e-4aac-acb0-b5ee82537134",
"_uuid": "09bc47f6cabf641be7880576dfae491655cc9889"
},
"source": [
"'cement' has the highest correlation with the area of 'concrete_compressive_strength'(which is a positive correlation), followed by 'superplasticizer', which is also a positive correlation, 'fly_ash' has the least correlation"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"_cell_guid": "f7471842-8ee8-4bd0-b777-6f53d74d18ce",
"_uuid": "bb4682284eb4c15498fafac57045a6b7aeab04b8",
"collapsed": true
},
"outputs": [],
"source": [
"dataset = dataframe.values\n",
"\n",
"\n",
"X = dataset[:,0:8]\n",
"Y = dataset[:,8] "
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"_cell_guid": "d44941b9-1549-40b3-8031-4c1ddecc7f51",
"_uuid": "52aa19773c275a861c41b9a3b8754165fd2c6cf0"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Number of Features: 3\n",
"Selected Features: [ True False False False True False False True]\n",
"Feature Ranking: [1 2 6 3 1 5 4 1]\n"
]
}
],
"source": [
"#Feature Selection\n",
"model = ExtraTreesRegressor()\n",
"rfe = RFE(model, 3)\n",
"fit = rfe.fit(X, Y)\n",
"\n",
"print(\"Number of Features: \", fit.n_features_)\n",
"print(\"Selected Features: \", fit.support_)\n",
"print(\"Feature Ranking: \", fit.ranking_) "
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "392adf2a-c8a8-448a-8e0b-2c77d1963b9c",
"_uuid": "5540c12212e8fcc7a6302542d3736b3a288f520f"
},
"source": [
"'cement', 'superplasticizer' and 'age' were top 3 selected features/feature combination for predicting 'Area'\n",
"using Recursive Feature Elimination, the 1st and 2nd selected features were atually among the attributes with the highest correlation with the 'concrete_compressive_strength'"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "25728ac2-5709-4c93-adcb-6e7c969b7745",
"_uuid": "2ff59720c0481ad5c47e79aad3499c6316a77e94",
"collapsed": true
},
"source": [
"**VISUALIZATION**"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"_cell_guid": "7be0f725-1f66-4cc9-92ae-5697e2017edf",
"_uuid": "e69f2aeb077bbfc27090f6768eb87018cc2e1dd7"
},
"outputs": [
{
"data": {
"text/plain": [
"(array([ 45., 133., 156., 181., 196., 112., 100., 52., 36., 19.]),\n",
" array([ 2.33 , 10.357, 18.384, 26.411, 34.438, 42.465, 50.492,\n",
" 58.519, 66.546, 74.573, 82.6 ]),\n",
" <a list of 10 Patch objects>)"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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T3Jbk1iRvnoZsSX4syZeS/EeX6/enIVeX4YQk/57kE9OSqcuxN8mXk+xKsmNasiV5cpKP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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f6e181f06a0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.hist((dataframe.concrete_compressive_strength))"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "418e6678-5f09-40d1-bea9-a2485e9902a6",
"_uuid": "dcc76d15afe5ca7d144a8a984270054167e120fa",
"collapsed": true
},
"source": [
"Most of the dataset's samples fall between 34 and 42 of 'concrete_compressive_strength' continous output class, with a positive skew"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"_cell_guid": "f35222c7-bcd7-448e-9cb0-9b0783bd4446",
"_uuid": "db07bd45f19fb9b23b85b1326e6f444e81b9b25f"
},
"outputs": [
{
"data": {
"text/plain": [
"array([[<matplotlib.axes._subplots.AxesSubplot object at 0x7f6dfcee0f60>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7f6dfce21f60>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7f6dfce441d0>],\n",
" [<matplotlib.axes._subplots.AxesSubplot object at 0x7f6dfcd6a828>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7f6dfccc99b0>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7f6dfccc99e8>],\n",
" [<matplotlib.axes._subplots.AxesSubplot object at 0x7f6dfcc23f98>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7f6dfcbe93c8>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7f6dfcb75908>]], dtype=object)"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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sWPMEqgF5j8PcuXOfNrPXwTo3xGVpe5WkB3G3tmn4EBjcT7sbd4OdBlxhZi8B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\nQRB0MP8fVIZgTB8GVwcAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f6e181f0390>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"dataframe.hist()"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"_cell_guid": "5ba18a46-1e71-451d-aa16-57c8b3a3c89e",
"_uuid": "1d1dbfbc9129a1b7f984623f4b92fb0e3421f832"
},
"outputs": [
{
"data": {
"text/plain": [
"array([[<matplotlib.axes._subplots.AxesSubplot object at 0x7f6dfcaf1588>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7f6dfc803ac8>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7f6dfc82b1d0>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7f6dfc74bac8>],\n",
" [<matplotlib.axes._subplots.AxesSubplot object at 0x7f6dfc75ceb8>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7f6dfc75cda0>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7f6dfc67b2e8>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7f6dfc5e4940>],\n",
" [<matplotlib.axes._subplots.AxesSubplot object at 0x7f6dfc547cc0>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7f6dfc4c2978>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7f6dfc4a72e8>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7f6dfc4646d8>]], dtype=object)"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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WorZS7UKIclTP5KbybEA1sjWPLauxL4EFLc3rOB7fUpn/NnNoGrgnEIddUfAy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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f6dfce8f0b8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"dataframe.plot(kind='density', subplots=True, layout=(3,4), sharex=False, sharey=False)"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "18386aac-345b-48b4-812c-4ec8ead90053",
"_uuid": "37bffdba184f7e836a384011b567f0a28ec94c03"
},
"source": [
"None of the features have a Guassian Distribution. \n",
"All of them have a positive skew except 'water' and 'fine_aggregate', which have negative skews"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"_cell_guid": "f2047974-d865-43d7-865a-bd257422c7b5",
"_uuid": "bbd32ebd66a7572174813371851d762261c4b275"
},
"outputs": [
{
"data": {
"text/plain": [
"cement Axes(0.125,0.657941;0.168478x0.222059)\n",
"blast_furnace_slag Axes(0.327174,0.657941;0.168478x0.222059)\n",
"fly_ash Axes(0.529348,0.657941;0.168478x0.222059)\n",
"water Axes(0.731522,0.657941;0.168478x0.222059)\n",
"superplasticizer Axes(0.125,0.391471;0.168478x0.222059)\n",
"coarse_aggregate Axes(0.327174,0.391471;0.168478x0.222059)\n",
"fine_aggregate Axes(0.529348,0.391471;0.168478x0.222059)\n",
"age Axes(0.731522,0.391471;0.168478x0.222059)\n",
"concrete_compressive_strength Axes(0.125,0.125;0.168478x0.222059)\n",
"dtype: object"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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lq8HOLIwxJg0yKTDEYmcWxhhjErIzC5MR6tNefmSL5mnIiTFNkwULE3qxLsAW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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f6dfc722438>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"dataframe.plot(kind='box', subplots=True, layout=(3,4), sharex=False, sharey=False)\n"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"_cell_guid": "88ebfbbb-503e-43da-85fc-18c663417711",
"_uuid": "29a1bd6ad16d7dbb6331289209839f998ee7c08e"
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py:1: FutureWarning: 'pandas.tools.plotting.scatter_matrix' is deprecated, import 'pandas.plotting.scatter_matrix' instead.\n",
" \"\"\"Entry point for launching an IPython kernel.\n"
]
},
{
"data": {
"text/plain": [
"array([[<matplotlib.axes._subplots.AxesSubplot object at 0x7f6dfbcdee10>,\n",
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" [<matplotlib.axes._subplots.AxesSubplot object at 0x7f6dfb97cb38>,\n",
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" <matplotlib.axes._subplots.AxesSubplot object at 0x7f6dfaf214a8>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7f6dfae81828>],\n",
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" <matplotlib.axes._subplots.AxesSubplot object at 0x7f6dfaddce10>,\n",
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" <matplotlib.axes._subplots.AxesSubplot object at 0x7f6dfad2b780>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7f6dfacbdeb8>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7f6dfac774e0>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7f6dfabc9c88>,\n",
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]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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ug/q+QQ3+2W0tXLqoEjA1ZwHMKc+iItfNpQsHrRTV+R6uPKmcuGZwsDtIrts0IfojKllO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\n3yF6PB6PxwP4DtHj8Xg8HgD+P64Av3NanU2MAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f6dfc863080>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"scatter_matrix(dataframe)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"_cell_guid": "f9fdc16a-8c0e-4fd4-b445-5fb6362f747e",
"_uuid": "2fed58303ffd232b0a3d98a8b52fbb995fe3dd42",
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"_cell_guid": "15751db7-39dd-4606-ac0d-9699400b101e",
"_uuid": "4a4c948811a19cc874c2bea2afc88a2abf6daabd",
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.1"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
| 0001/480/1480111.ipynb | s3://data-agents/kaggle-outputs/sharded/034_00001.jsonl.gz |
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"_cell_guid": "1892653c-3d58-49ab-a836-cae567fde0c2",
"_uuid": "c8a28fde33b4867bd368f9dbcded89face3a34e4"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"age_gender_bkts.csv\n",
"countries.csv\n",
"sample_submission.csv\n",
"sessions.csv\n",
"test_users.csv\n",
"train_users_2.csv\n",
"\n"
]
}
],
"source": [
"import numpy as np\n",
"import pandas as pd \n",
"import seaborn as sns\n",
"import matplotlib.pyplot as plt\n",
"import matplotlib as mpl\n",
"%matplotlib inline\n",
"from sklearn.model_selection import train_test_split\n",
"\n",
"from subprocess import check_output\n",
"print(check_output([\"ls\", \"../input\"]).decode(\"utf8\"))\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"1. Basic ** Data pre-processing** :\n",
" * 1(a) Loading the csv files into pandas data frame\n",
" * 1(b) Dividing data into Train and Test data"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"1(a). Loading the csv files into pandas data frame"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# data from csv files is imported to pandas data frames\n",
"data_train_org = pd.read_csv(\"../input/train_users_2.csv\")\n",
"data_countries = pd.read_csv(\"../input/countries.csv\")\n",
"data_sessions = pd.read_csv(\"../input/sessions.csv\")\n",
"data_agegender = pd.read_csv(\"../input/age_gender_bkts.csv\")"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(213451, 16)\n"
]
}
],
"source": [
"print(data_train_org.shape)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" 1(b).Dividing the data into** train data** and ** test data**"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"170760 items in training data, 42691 in test data\n"
]
}
],
"source": [
"data_train, data_test = train_test_split(data_train_org, test_size=0.2)\n",
"print(\"%d items in training data, %d in test data\" % (len(data_train), len(data_test)))"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Index(['id', 'date_account_created', 'timestamp_first_active',\n",
" 'date_first_booking', 'gender', 'age', 'signup_method', 'signup_flow',\n",
" 'language', 'affiliate_channel', 'affiliate_provider',\n",
" 'first_affiliate_tracked', 'signup_app', 'first_device_type',\n",
" 'first_browser', 'country_destination'],\n",
" dtype='object')\n"
]
}
],
"source": [
"print(data_train.columns)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"122138 FEMALE\n",
"176260 FEMALE\n",
"185486 -unknown-\n",
"129144 FEMALE\n",
"68362 FEMALE\n",
"74056 -unknown-\n",
"195011 FEMALE\n",
"400 -unknown-\n",
"40219 -unknown-\n",
"177075 FEMALE\n",
"6119 MALE\n",
"93269 MALE\n",
"177996 -unknown-\n",
"109943 -unknown-\n",
"169539 MALE\n",
"80253 -unknown-\n",
"14872 FEMALE\n",
"184348 MALE\n",
"178022 MALE\n",
"139656 MALE\n",
"152433 FEMALE\n",
"29691 -unknown-\n",
"18890 FEMALE\n",
"54414 FEMALE\n",
"134211 MALE\n",
"13445 -unknown-\n",
"210353 -unknown-\n",
"116535 -unknown-\n",
"57533 FEMALE\n",
"97183 MALE\n",
" ... \n",
"51227 -unknown-\n",
"210598 -unknown-\n",
"212590 -unknown-\n",
"30707 FEMALE\n",
"140431 -unknown-\n",
"107977 -unknown-\n",
"108133 -unknown-\n",
"204384 -unknown-\n",
"81817 -unknown-\n",
"88677 -unknown-\n",
"14617 -unknown-\n",
"52814 -unknown-\n",
"165406 MALE\n",
"201344 -unknown-\n",
"110327 FEMALE\n",
"67150 MALE\n",
"56953 -unknown-\n",
"53597 -unknown-\n",
"209212 FEMALE\n",
"132804 -unknown-\n",
"204494 MALE\n",
"42702 -unknown-\n",
"102287 MALE\n",
"27905 FEMALE\n",
"44877 FEMALE\n",
"140048 FEMALE\n",
"198407 MALE\n",
"49669 MALE\n",
"94666 -unknown-\n",
"31981 MALE\n",
"Name: gender, Length: 170760, dtype: object\n"
]
}
],
"source": [
"print(data_train['gender'])"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.1"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
| 0001/480/1480185.ipynb | s3://data-agents/kaggle-outputs/sharded/034_00001.jsonl.gz |
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"_cell_guid": "50249ab0-c2c7-42b6-9095-db64e171cc39",
"_uuid": "18228c9c8dd90a6832e8dabc034d4a0b67f6b2c5"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Reviews.csv\n",
"database.sqlite\n",
"hashes.txt\n",
"\n"
]
}
],
"source": [
"import numpy as np # linear algebra\n",
"import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
"import seaborn as sns\n",
"\n",
"from subprocess import check_output\n",
"print(check_output([\"ls\", \"../input\"]).decode(\"utf8\"))"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"_cell_guid": "3f15302e-87d8-42ca-9d95-2e7277dd0709",
"_uuid": "14c42f47de0c57c6b9cb4ef0fed459a997ae740a",
"collapsed": true
},
"outputs": [],
"source": [
"import sqlite3\n",
"import nltk\n",
"import string\n",
"import matplotlib.pyplot as plt\n",
"import matplotlib as mpl\n",
"%matplotlib inline\n",
"import numpy as np"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "c0c75a60-9a4a-4ac3-a3eb-95063529a486",
"_uuid": "a451f17d38035e19b0094f0e592d5ed374c0a3bd"
},
"source": [
"**Task -1** ( Basic exploratory data analysis )"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"_cell_guid": "42797551-cbe6-4b28-b763-c8cf08f63fde",
"_uuid": "968e882e75345c16387b24d0a9366b6b526c4149"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" Score Id UserId\n",
"0 5 1 A3SGXH7AUHU8GW\n",
"1 1 2 A1D87F6ZCVE5NK\n",
"2 4 3 ABXLMWJIXXAIN\n",
"3 2 4 A395BORC6FGVXV\n",
"4 5 5 A1UQRSCLF8GW1T\n",
"5 4 6 ADT0SRK1MGOEU\n",
"6 5 7 A1SP2KVKFXXRU1\n",
"7 5 8 A3JRGQVEQN31IQ\n",
"8 5 9 A1MZYO9TZK0BBI\n",
"9 5 10 A21BT40VZCCYT4\n",
"10 5 11 A3HDKO7OW0QNK4\n",
"11 5 12 A2725IB4YY9JEB\n",
"12 1 13 A327PCT23YH90\n",
"13 4 14 A18ECVX2RJ7HUE\n",
"14 5 15 A2MUGFV2TDQ47K\n",
"15 5 16 A1CZX3CP8IKQIJ\n",
"16 2 17 A3KLWF6WQ5BNYO\n",
"17 5 18 AFKW14U97Z6QO\n",
"18 5 19 A2A9X58G2GTBLP\n",
"19 5 20 A3IV7CL2C13K2U\n"
]
},
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7fe35517f5c0>"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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ZuQq4se3w1VQb9r9JNQO20V7AHcCKuvyuetN/H/AgsNuwuivqX7GJckmSpElt1D1lEbEz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\nRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fe355ecfe10>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"data = sqlite3.connect('../input/database.sqlite')\n",
"messages = pd.read_sql_query(\"\"\"\n",
"SELECT Score, Id,userId\n",
"FROM Reviews\n",
"WHERE Score \n",
"\"\"\", data)\n",
"print(messages.head(20))\n",
"messages.groupby('Score')['Id'].count().plot(kind='bar',color=['r','g','y','b'],title='Label Distribution',figsize=(10,6))\n"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"_cell_guid": "54c96843-1bf4-4ee3-b2f9-369d8db6f072",
"_uuid": "1f2d5be5880250e9f1b07178b196e1362d5cf09b"
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7fe34241de80>"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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Aqd3l5qx5Qd/Sc1bmtnrsltRZJG3Q7qkDpLSxqbe1PgKcHULoI1uzNA68t2Gp\nWp8jStIMyPVUF83d/5ePjN184OUTD+7c1QtGpRbW1SNKueom7AUXQlgA5GKMDzYuUuvLl4tfAt6d\nOofUKapVJibue96FY7fttzx1FknPMAb0jQwNTKYOksLGznp7S53jAMQYv9GATO3AqTdpBuVy9M7a\n6fblPfMfvnD0uiMOo9ozJ3UmSX80m+z33p2pg6Swsam3DZ3CWwW6tSg59SY1QM+8x5b1LT3n6tVX\nL3sOY307ps4j6Y92w6L0TDHGNwOEEJ4bY7y7OZHagiNKUoPkZo0f0HfwirvWXH/YDZOPb78kdR5J\nAOyUOkAq0z3r7YyGpmg/O6QOIHWyXK6685x9Lt2td+FtF6fOIgnIpt+60nTPersxhPAt4CJgzdqD\nXbxGyauhSw2Wy7H17N2vP7x3m4dWrPndwS+GXC51JqmLdW1Rmu6I0lxgAngR2bqlo4FljQrVBiZS\nB5C6QS5HrnfBvcvnHnj+pfSMP5E6j9TFurYoTWtEKcb45hBCD7AwxnhPgzO1g648RVJKpadv1eF9\nS8+JY7ft+wjVHi97IjVZdaJ3PHWGVKZVlEIIxwL/DowCS0IInwPOijH+tJHhWpgjSlKT5Xonw5zF\n16SOIXWruakDpDLdqbdTgcOBtWe+/RPw0YYkag+OKEmSuslY6gCpTLcoPR5jvHftFzHGB5iyqLsL\nOaIkSeomTr1txKoQwnIgF0LYHngdsLpxsVqeRUmS1E26dkRpukXp3UAJOBT4PXAB8I5GhWoDXdus\nJUld6aHUAVKZ7llvtwN/tvbrEEJPjLGb1+k8ACxKHUKSpCa5I3WAVKZ71tuJwNbAV4AVwPNCCJ+K\nMZYamK2V3ZU6gCRJTdS1RWm6i7nfSbY9wJ8D1wB7AIVGhWoDFiVJUrd4qFIoPZk6RCrTLUqrYoyj\nwP8BKrVpt26+jEdXXkFZktSVunY0CaZflAghfAk4ClgRQjgC6GtYqtZ3W+oAkiQ1SVcXpQ2uUQoh\n7FZ7+GHgMOB7wDxgd+BdjY3W0n6fOoAkSU1iUdqAX5JNsU29avcOwNnACY0K1QZ+lzqAJElNYlGq\nJ8b4vHWP1S6O+05gCHhzg3K1tEqhdF++XHwMeFbqLJIkNVhXDw5Me43SWjHGydq2AHs0IE87uSp1\nAEmSmuCS1AFS2uSiNEU3n/UG2bSkJEmd7N5KoXRL6hApbVZRCiG8HrhvhrO0G4uSJKnTdfVoEmz8\nrLfbeeacbKPTAAAO3klEQVTI0fbAr4DXNypUm7godQBJkhrs4tQBUtvYWW/L1nPssRhj114cb61K\nofRAvlyMQEidRZKkBnFEaUNPxhjdWHHDLsSiJEnqTOPAZalDpLYli7nlOiVJUue6upuv8baWRWnL\nWJQkSZ3qwtQBWoFFaQtUCqUb6fIdSyVJHeuHqQO0AovSlvt+6gCSJM2w+4DzU4doBRalLfe91AEk\nSZphP6gUShOpQ7QCi9IWqhRKvwJuTp1DkqQZ5GxJjUVpZpRTB5AkaYbcB6xIHaJVWJRmhtNvkqRO\n4bTbFBalGVAplK4CrkudQ5KkGeC02xQWpZnj9Jskqd3di9NuT2NRmjln8MwLCEuS1E6+4rTb01mU\nZkilUPo9MJI6hyRJm2k18KXUIVqNRWlm/XPqAJIkbaYzKoXSfalDtBqL0gyqFEq/BC5KnUOSpE1U\nBf4ldYhWZFGaeZ9JHUCSpE30/yqFkmdvr4dFaeYNAzF1CEmSNoGjSXVYlGZYpVCqAkOpc0iSNE2/\nrRRKZ6UO0aosSo3xLeCe1CEkSZoGR5M2wKLUAJVCaRT4XOockiRtxNVk+wCqDotS43weuCV1CEmS\nNuB9bjC5YRalBqkUSquB96fOIUlSHT9xbdLGWZQaqFIo/TdwbuockiStYww4OXWIdmBRary/BRzW\nlCS1klKlUHIrm2mwKDVYpVC6Cvha6hySJNWsBD6ROkS7sCg1x0fI/ocpSVJqn6gUSg+lDtEuLEpN\nUCmUHgT+IXUOSVLXuwH4cuoQ7cSi1DxfBn6bOoQkqWtNACdUCqWx1EHaiUWpSSqF0jjwRmB16iyS\npK50aqVQ+lXqEO3GotRElULpGuBDqXNIkrrOFcApqUO0I4tS8/0b8IvUISRJXWM18H9rMxvaRBal\nJqsUSlXgRMAzDiRJzfChSqF0feoQ7cqilEClULoLeEfqHJKkjncO2UyGNlOuWq2mztC18uXifwAn\npM4hSepIjwAHVAql21MHaWeOKKV1EnBL6hCSpI70LkvSlrMoJVQplB4D8sCq1FkkSR3l05VC6Xup\nQ3QCi1JilULpcuDNqXNIkjrGT4C/Tx2iU1iUWkClUCrj/haSpC13HfD6SqE0mTpIp7AotY5/AL6f\nOoQkqW09BBxfW9ahGeJZby0kXy5uBVwAvCB1FklSWxkHXlEplM5OHaTTOKLUQiqF0ipgALgrdRZJ\nUlt5nyWpMSxKLaZSKN1JVpY8E06SNB1fqxRKX0gdolNZlFpQ7Uy4EwAX40mSNuQnwLtTh+hkFqUW\nVSmUvk92mRMXkUmS1uc84LVe7LaxLEotrFIo/Tv+pSBJeqbLyM5wW506SKezKLW4SqF0OvA3qXNI\nklrGNcAr3QagOSxKbaBSKH0eeH/qHJKk5K4HXloplB5MHaRbWJTaRKVQ+izw4dQ5JEnJRODYSqF0\nX+og3cSi1EYqhdKpeKkTSepGN5GVpHtSB+k2FqU2UymUPg58KnUOSVLTXAu8pFIouRlxAhalNlQp\nlD4EfCR1DklSw10ALKttRqwEvNZbG8uXi28DTgd6U2eRJM24HwKvdwuAtBxRamOVQunrwGsA/yOS\npM5yOvAaS1J6jih1gHy5+GLgR8D2qbNIkrbYxyuFkifutAiLUofIl4tLgP8B9kidRZK0WSaAYqVQ\n+lrqIHqKRamD5MvFhcAIcFjqLJKkTbIKeF2lUPpx6iB6OtcodZDaJmTHkE3DSZLaw11keyRZklqQ\nRanDVAqlVcCrgY8Dk4njSJI27HzgkEqhdEnqIFo/p946WL5cPA44A9ghdRZJ0jN8DvhApVAaTx1E\n9VmUOly+XNwNOBM4NHUWSRIATwBvqxRK30sdRBvn1FuHqxRKfwCOBr6SOoskiZuAwy1J7cMRpS6S\nLxffRLaJ2Vaps0hSF/ox8KZKofRI6iCaPkeUukilUPoWcDjwu9RZJKmLTJJdn/NVlqT244hSF8qX\ni9sC/w78ReosktThbgZOqBRKF6YOos1jUepi+XLxjcAXgO1SZ5GkDvQ14H2VQunx1EG0+SxKXS5f\nLu4CfB14ReosktQh7iE7q+2nqYNoy1mUBEC+XHwHMATMT51FktrYmcC7KoXSg6mDaGZYlPRH+XJx\nD+CbwPLUWSSpzTwMnFQplL6TOohmlme96Y8qhdItwEuAvyW7QKMkaePOAg6wJHUmR5S0XvlycW/g\nP8m2E5AkPdNK4EPAVyuFkr9MO5RFSXXly8Ue4B3APwELEseRpFZRBf4D+GClULo/cRY1mEVJG5Uv\nF3cATgPeitO1krrbb4G/qhRKv0wdRM1hUdK05cvFQ4Ev4QV2JXWfR4GPAV+sFEoTqcOoeSxK2iS1\n6bi3ko0w7ZA4jiQ1w3eBkyuF0t2pg6j5LEraLPlycQHZ2qV34HScpM50Pdk027mpgygdi5K2SL5c\nfAHwRTw7TlLneJDsD8EvVgqlsdRhlJZFSTMiXy7+BfBJYJ/UWSRpMz0B/Avw2Uqh9GjqMGoNFiXN\nmHy52Av8X+AfgN3TppGkaRsDvgL8Y6VQujd1GLUWi5JmXL5cnAO8E/gIsDBxHEmqZxL4L+CjtSsT\nSM9gUVLD5MvFeWSXQ3k/sG3iOJI01f8AH6oUSlelDqLWZlFSw+XLxe2BDwInAVsnjiOpu10E/F2l\nULogdRC1B4uSmiZfLj6XrDC9DZiXOI6k7vIL4FOVQumc1EHUXixKarraHkx/XbvtmDiOpM41CZwJ\nfLpSKF2ZOozak0VJyeTLxa2AtwDvAxYnjiOpc4wC/wl8plIo/S51GLU3i5KSq20r8BrgA8AhieNI\nal+PAqcDn6sUSvekDqPOYFFSS8mXi39CVpheljqLpLZxL/CvQKlSKD2SOow6i0VJLSlfLi4FBslG\nmuYmjiOpNV1CNoJUrhRKq1OHUWeyKKml5cvFZwMnkl18d6+0aSS1gCeAM8hGj36TOow6n0VJbSFf\nLuaAY4F3AQPA7LSJJDXZtUAJ+LbXYVMzWZTUdvLl4k7AW4G3A4vSppHUQGvITu8/3Q0ilYpFSW0r\nXy72AC8nG2X6M6A3bSJJM+QWsovUfqNSKN2fOoy6m0VJHSFfLu4CnAC8HtgvcRxJm+5R4PvAt4Hz\nK4WSv5zUEixK6jj5cvFAssL0OmD3xHEk1TcO/IysHP24UiitSpxHegaLkjpWbQH4UWSl6bXAs9Mm\nkgRUyS5M+1/A9yuF0n2J80gbZFFSV8iXi7PI1jP9JfAqYH7aRFLX+Q1ZOfpepVD6Q+ow0nRZlNR1\n8uXi1kA/2dTcccBWaRNJHakKXAYMAz+oFEo3JM4jbRaLkrpa7cK8Lyfbm6kfp+ekLbEaOJusHI14\nvTV1AouSVFPbbuAonipNe6dNJLWFB4CfAD8Gfl4plJ5InEeaURYlqY58ubgn8KdkezS9GJiTNpHU\nMm4kGzX6MXBRpVCaTJxHahiLkjQN+XJxPvAy4JXAS4A90yaSmmolcC7ZtNpZlULpxsR5pKaxKEmb\nIV8uPo+sMB1bu98tbSJpRj0BXEhWjM4GfuOokbqVRUmaAflycTFPlaaXAM9Nm0jaJGPAJWSl6Bzg\nkkqhNJY2ktQaLEpSA+TLxSU8VZyWAzumTSQ9zSrgCrKNH88BLnQRtrR+FiWpCfLl4h7AYbXbi4BD\ncP8mNUeVbPH1pWSjRpcCV1UKpfGkqaQ2YVGSEqjtFL4/WWlaW6D2BXpS5lJHeIinl6JfVQqllWkj\nSe3LoqSWF0I4BvjrGONrUmdppNqZdS/kqeJ0ELAYy5Pquwe4GrgGuBK4tFIo3ZQ2ktRZZqUOIClT\nKZQeB86r3YA/7hy+D9no09rbfniWXbd5nKwMXc1TxejqSqH0QNJUUhdwRElNEUI4Edg/xnhyCGE+\n2f/Rl4BXA5PASIzx1BDC0cCpZGfh3A68HTiS2ohSCOHVwCAwDlweYxwMIewGfAeYICv/byRbl/G0\nYzHG25r2gRssXy5uQ1aYppan/YGdUubSFlsF/J5nlqJbK4WS/2ctJeCIklI6mew0+gngXbVjnwde\nGmN8KITwz8BrgTsBagXrI8ARMcbREEIlhHAU2TqfX8QYPxlCOKT2nkeu51jHFKVKofQocHHt9kf5\ncnEB2XTdYmCPdR7vBsxublKtx/1kZejm2v3Ux3dbiKTWYlFSSmcCZwHfBc4IIewE7AX8IIQAMI/s\nOlJ31l6/dsrpZ7XntwV2B34O/DCEsB1wZozx4hDC4+sea97HSqdSKD1Etpj38nWfy5eLvcCuPLNI\n7UH277gQ6G1a2M5UBR4E7q7dbmadQlQplB5LF0/SprIoqVmm/pU8GyDGWAwhLAHyZOtyjgPujDEe\nM/Uba4u5AdYAV8QYj1v3zUMIBwEvB04LIXwjxvit9R2b2Y/UXiqF0gTZqNptZJejeJraRYGfDTyn\ndttpyuN1v14A5JoSvDWsIVs4fQ9PlaD1Pb7XjRqlzmJRUrM8ylO7VS8Dtg0hfCzGeApwSgjhxWRT\ncIQQ9o0xXhdCOAlYMeU9IrBPCGFhjPG+EMIngK8CRwM3xxh/FEJ4AMiHENasewzo6qK0MbVLVNxX\nu121odfmy8XZZCNQC8lG9p4FbLMJt/lkFxmeTWML1zgwWrutAh7ZyO3R9Rx7GFjplJjUnVzMraYI\nIWxDtgPw48BPgWLt/kW1YxfFGD8SQlgGDJH9BX8X8CbgCJ6+mPvvyX7x/Ro4CVgKnF57nwngPWSb\nOT7tWIzx+uZ8Wm2K2kjWbLI/3GZNeVzvWJWsAE3U7qc+HuOpYjTq9ckkbSmLkiRJUh1uZCdJklSH\nRUmSJKkOi5IkSVIdFiVJkqQ6LEqSJEl1WJQkSZLqsChJkiTVYVGSJEmqw6IkSZJUh0VJkiSpDouS\nJElSHRYlSZKkOixKkiRJdViUJEmS6rAoSZIk1WFRkiRJqsOiJEmSVIdFSZIkqQ6LkiRJUh0WJUmS\npDosSpIkSXVYlCRJkuqwKEmSJNVhUZIkSarDoiRJklSHRUmSJKkOi5IkSVIdFiVJkqQ6LEqSJEl1\nWJQkSZLqsChJkiTVYVGSJEmqw6IkSZJUh0VJkiSpDouSJElSHRYlSZKkOixKkiRJdViUJEmS6vj/\nqZ/201FUQpwAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fe34241d668>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"messages = pd.read_sql_query(\"\"\"\n",
"SELECT \n",
" Score, \n",
" Summary,\n",
" Userid,\n",
" HelpfulnessNumerator as Helpnum, \n",
" HelpfulnessDenominator as Helpdenom\n",
"FROM Reviews \n",
"\"\"\", data)\n",
"\n",
"messages[\"helpFactor\"] = ( messages[\"Helpnum\"]/messages[\"Helpdenom\"]).apply(lambda n: \"useful\" if n > 0.8 else \"useless\")\n",
"messages.groupby('helpFactor')['UserId'].count().plot(kind='pie',legend = True ,title='Label Distribution',figsize=(10,6))"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"_cell_guid": "c35f40b5-5cd2-4687-b2c1-b768f94273e8",
"_uuid": "a47bca037d470127865aac7ac588d961f132eb05"
},
"outputs": [
{
"data": {
"image/png": 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"text/plain": [
"<matplotlib.figure.Figure at 0x7fe354a96fd0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"#3\n",
"messages = pd.read_sql_query(\"\"\"\n",
"SELECT \n",
" Score, \n",
" Summary,\n",
" Userid,\n",
" HelpfulnessNumerator as Helpnum, \n",
" HelpfulnessDenominator as Helpdenom\n",
"FROM Reviews \n",
"\"\"\", data)\n",
"messages[\"helpFactor\"] = ( messages[\"Helpnum\"]/messages[\"Helpdenom\"]).apply(lambda n: \"useful\" if n > 0.8 else \"useless\")\n",
"#messages.groupby('Score')['helpFactor'].count().plot(kind='bar',legend = True ,title='Label Distribution',figsize=(10,6))\n",
"sns.distplot(messages[\"Score\"], kde=False, color=\"b\")\n",
"plt.show()\n",
"messages[\"helpFactorNum\"] = ( messages[\"Helpnum\"]/messages[\"Helpdenom\"])"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"_cell_guid": "8ba51e25-63dc-41f0-a65c-c1cf80db5189",
"_uuid": "070d82fb1042276391516be378e989a47987844b"
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7fe3510c75f8>"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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ezZe23M76uy7lvWvfz5+e+ecsaV5CW327K79L0xFLxjgaPcovXrmHr279Eol0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\nIlLFlKRFRKqYkrSISBX7/9fDNGULb1voAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fe356822198>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.distplot(messages[\"Score\"], hist=False, color=\"g\", kde_kws={\"shade\": True})"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"_cell_guid": "3b36b194-6c5c-4146-b459-27d4b8db8793",
"_uuid": "825224d94e41cb258426886ebf02d6b0319416b2"
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7fe351374cc0>"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAdgAAAFkCAYAAACD0SqXAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fe372dfcc18>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.set(style=\"ticks\")\n",
"sns.boxplot(x=messages[\"Score\"],hue=messages[\"helpFactor\"], data=messages, palette=\"Set3\")\n"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"_cell_guid": "ec055ec9-4d84-4762-8dfe-c827dbcccbb7",
"_uuid": "8a50b051bdba4663e2d2ade8bb2a05c430bfc18d",
"collapsed": true
},
"outputs": [],
"source": [
"messages = pd.read_sql_query(\"\"\"\n",
"SELECT \n",
" Score, \n",
" Summary,\n",
" Text\n",
"FROM Reviews \n",
"\"\"\", data\n",
" )"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "54d1b4e5-b686-47dc-93eb-e98695cf24c9",
"_uuid": "7739a97c2df776779cd15754eb69ebd743dedc26",
"collapsed": true
},
"source": [
"** Data preprocessing : **\n",
" * Remove Html tags\n",
" * Convert Capital to small letters\n",
" * Remove stop words "
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"_cell_guid": "fd2d8693-4b4c-4833-bad5-daf5c9cfb961",
"_uuid": "97b45bd9649db403be9e18f4c1e8346fe49d8f6d"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"454763 items in training data, 113691 in test data\n"
]
}
],
"source": [
"# Data pre-processing\n",
"from sklearn.feature_extraction.text import CountVectorizer, TfidfTransformer\n",
"from sklearn.model_selection import train_test_split\n",
"from sklearn.metrics import confusion_matrix\n",
"import re\n",
"import string\n",
"import nltk\n",
"cleanup_re = re.compile('<.*?>') \n",
"cleanup_re = re.compile('[^a-z]+')\n",
"def cleanup(sentence):\n",
" sentence = sentence.lower()\n",
" sentence = cleanup_re.sub(' ', sentence).strip()\n",
" return sentence\n",
"\n",
"messages[\"Summary_Clean\"] = messages[\"Summary\"].apply(cleanup)\n",
"messages[\"Text\"] = messages[\"Text\"].apply(cleanup)\n",
"messages[\"Sentiment\"] = messages[\"Score\"].apply(lambda score: \"positive\" if score > 3 else \"negative\")\n",
"\n",
"train, test = train_test_split(messages, test_size=0.2)\n",
"print(\"%d items in training data, %d in test data\" % (len(train), len(test)))"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"_cell_guid": "f5e5980b-f200-4f87-bdd0-38a2369800b7",
"_uuid": "bd76916d3aae340a1ed029e8d6a2e1013ee1f91a",
"collapsed": true
},
"outputs": [],
"source": [
"from wordcloud import WordCloud, STOPWORDS\n",
"\n",
"stop_words = STOPWORDS\n",
"count_vect = CountVectorizer(min_df = 1, ngram_range = (1, 4))\n",
"X_train_counts = count_vect.fit_transform(train[\"Summary_Clean\"])\n",
"\n",
"tfidf_transformer = TfidfTransformer()\n",
"X_train_tfidf = tfidf_transformer.fit_transform(X_train_counts)\n",
"\n",
"X_new_counts = count_vect.transform(test[\"Summary_Clean\"])\n",
"X_test_tfidf = tfidf_transformer.transform(X_new_counts)\n",
"\n",
"y_train = train[\"Sentiment\"]\n",
"y_test = test[\"Sentiment\"]\n",
"prediction = dict()"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"_cell_guid": "caf6a9a3-e0ba-43f4-a7be-8ac8c88a918f",
"_uuid": "20485ed3dda98a35457612081492d34ccab91411",
"collapsed": true
},
"outputs": [],
"source": [
"import re\n",
"from nltk.corpus import stopwords\n",
"from nltk.stem import PorterStemmer\n",
"\n",
"ps = PorterStemmer()\n",
"def preProcessString(text):\n",
" # remove all html tags\n",
" text = re.sub('<.*?>', ' ', str(text))\n",
" \n",
" # remove all special characters\n",
" text = re.sub('[^A-Za-z0-9]+', ' ', text)\n",
" \n",
" # converting all text into small letters and store them as words for furthur processing\n",
" text_list = text.lower().split()\n",
" \n",
" # removing stopwords from the text\n",
" english_stop_words = set(stopwords.words('english'))\n",
" # we have used set instead of list because, set uses hashing to store the words. So lookup is O(1).\n",
" # where as for list the look up time is O(n) (ie., make things faster in list comprehension below)\n",
" text_list = [word for word in text_list if word not in english_stop_words]\n",
" \n",
" # stemming the words (removing prefix and postfix) using Porter stemming algorithm..\n",
" text_list = [ps.stem(word) for word in text_list]\n",
" \n",
" return ' '.join(text_list)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"_cell_guid": "38be382b-32a2-4ee1-a8f3-6c82177b69f0",
"_uuid": "84c375a4732e8f41330627dfebffd6a6a6bd1064"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0 i have bought several of the vitality canned d...\n",
"1 product arrived labeled as jumbo salted peanut...\n",
"2 this is a confection that has been around a fe...\n",
"3 if you are looking for the secret ingredient i...\n",
"4 great taffy at a great price there was a wide ...\n",
"5 i got a wild hair for taffy and ordered this f...\n",
"6 this saltwater taffy had great flavors and was...\n",
"7 this taffy is so good it is very soft and chew...\n",
"8 right now i m mostly just sprouting this so my...\n",
"9 this is a very healthy dog food good for their...\n",
"10 i don t know if it s the cactus or the tequila...\n",
"11 one of my boys needed to lose some weight and ...\n",
"12 my cats have been happily eating felidae plati...\n",
"13 good flavor these came securely packed they we...\n",
"14 the strawberry twizzlers are my guilty pleasur...\n",
"15 my daughter loves twizzlers and this shipment ...\n",
"16 i love eating them and they are good for watch...\n",
"17 i am very satisfied with my twizzler purchase ...\n",
"18 twizzlers strawberry my childhood favorite can...\n",
"19 candy was delivered very fast and was purchase...\n",
"20 my husband is a twizzlers addict we ve bought ...\n",
"21 i bought these for my husband who is currently...\n",
"22 i can remember buying this candy as a kid and ...\n",
"23 i love this candy after weight watchers i had ...\n",
"24 i have lived out of the us for over yrs now an...\n",
"25 product received is as advertised br br a href...\n",
"26 the candy is just red no flavor just plan and ...\n",
"27 i was so glad amazon carried these batteries i...\n",
"28 i got this for my mum who is not diabetic but ...\n",
"29 i don t know if it s the cactus or the tequila...\n",
" ... \n",
"568424 i ve tried several violet flavored candies in ...\n",
"568425 this candy has a very good flavor it is quite ...\n",
"568426 the candy is tasty but they totally scam you o...\n",
"568427 i had been looking for the violet candy with t...\n",
"568428 these are very pricey so i only enjoy them now...\n",
"568429 these candies have a mild flavor when compared...\n",
"568430 this product is a bit pricey for the amt recei...\n",
"568431 definitely not worth buying flavored water wit...\n",
"568432 i thought this soup would be more like a chill...\n",
"568433 i just bought this soup today at my local groc...\n",
"568434 this soup is mostly broth although it has a ki...\n",
"568435 it is mostly broth with the advertised cup of ...\n",
"568436 in the past i would have to buy a large quanti...\n",
"568437 ammonium bicarbonate in a nice little package ...\n",
"568438 if you haven t ever used ammonium bicarbonate ...\n",
"568439 we need this for a recipe my wife is intereste...\n",
"568440 indie candy s gummies are absolutely delicious...\n",
"568441 quick and easy had similar gulasch in guest ho...\n",
"568442 this product is great gives you so much energy...\n",
"568443 i love this tea i first discovered the pleasur...\n",
"568444 as a foodie i use a lot of chinese spice powde...\n",
"568445 you can make this mix yourself but the star an...\n",
"568446 i had ordered some of these a few months back ...\n",
"568447 hoping there is no msg in this this tastes ext...\n",
"568448 my only complaint is that there s so much of i...\n",
"568449 great for sesame chicken this is a good if not...\n",
"568450 i m disappointed with the flavor the chocolate...\n",
"568451 these stars are small so you can give of those...\n",
"568452 these are the best treats for training and rew...\n",
"568453 i am very satisfied product is as advertised i...\n",
"Name: Text, Length: 568454, dtype: object\n"
]
}
],
"source": [
"#messages[\"Text\"] = messages[\"Text\"].apply(preProcessString)\n",
"print(messages[\"Text\"])"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"_cell_guid": "108c7f0b-7195-4940-a322-57c2626a2499",
"_uuid": "136f0ac07f44d4a77957e946b6718fee746426f6",
"collapsed": true
},
"outputs": [],
"source": [
"from wordcloud import WordCloud, STOPWORDS\n",
"stopwords = set(STOPWORDS)\n",
"mpl.rcParams['font.size']=12 \n",
"mpl.rcParams['savefig.dpi']=100 \n",
"mpl.rcParams['figure.subplot.bottom']=.1 \n",
"\n",
"\n",
"def show_wordcloud(data, title = None):\n",
" wordcloud = WordCloud(\n",
" background_color='white',\n",
" stopwords=stopwords,\n",
" max_words=200,\n",
" max_font_size=40, \n",
" scale=3,\n",
" random_state=1 \n",
" ).generate(str(data))\n",
" \n",
" fig = plt.figure(1, figsize=(8, 8))\n",
" plt.axis('off')\n",
" if title: \n",
" fig.suptitle(title, fontsize=20)\n",
" fig.subplots_adjust(top=2.3)\n",
"\n",
" plt.imshow(wordcloud)\n",
" plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"_cell_guid": "fe4f951d-6f6e-4e65-b831-f5b6573a1b63",
"_uuid": "1f60879ffa95f76d7766e78f532a9bc591059b5e"
},
"outputs": [
{
"data": {
"image/png": 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XdRtrIgWl/cpNGNLCEa5WFgiJjsWux89px/U6JhYvf8ZAX00V3xKS0alu6QPt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\nRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fe357df00f0>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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P8R8mT33fDp9RO+BuMBLzurFHqawuZKfJRmp6tsR9SnL3hOxC4wJAq75U1b4o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\nJPbEE4cvpt0bM3Yfxo3rhK6OjZD1LR+Dh/jhzOmZSExMh/fW66RhnzD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sAM5Zp7EUow4A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\nSUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fe3099c76a0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"show_wordcloud(messages[messages.Score == 1][\"Summary_Clean\"], title = \"Negative reviews\")\n",
"show_wordcloud(messages[messages.Score == 5][\"Summary_Clean\"], title = \"Positive reviews\")"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "9bafa408-3c83-4b74-bcb9-e1fe27fc80f3",
"_uuid": "afafa463a5b45fbca0da8ac2a38760c6e7b496b5"
},
"source": [
"Divide data into train and test data "
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"_cell_guid": "ef512c28-db70-4adc-8390-ac7953375ad6",
"_uuid": "88c712595288352da581614d213321465feeff40"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"454763 items in training data, 113691 in test data\n"
]
}
],
"source": [
"train, test = train_test_split(messages, test_size=0.2)\n",
"print(\"%d items in training data, %d in test data\" % (len(train), len(test)))"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "38bd207d-8edb-4727-ac94-3683812ee785",
"_uuid": "047a6ee922c9f17b28e017c4ee64dd0156874737"
},
"source": [
"**Task 3 **( To perform Bernoulli Naive Bayes on the Train data after tfidf text summarisation )"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"_cell_guid": "0c0c4ab6-774a-4ec1-9de4-ca431856975d",
"_uuid": "ac9bc4c9eb68d5346fb64070dcd8b0bb9cd32f0f",
"collapsed": true
},
"outputs": [],
"source": [
"from sklearn.naive_bayes import BernoulliNB\n",
"model = BernoulliNB().fit(X_train_tfidf, y_train)\n",
"prediction['Bernoulli'] = model.predict(X_test_tfidf)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"_cell_guid": "3e8a1f5b-dc73-4f2f-a408-f9f7f5de4b19",
"_uuid": "aa1888cad3089dc7e347adbc679d1ede4c115b83"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The classification metric values for Bernoulli naive bayes classification are \n",
" precision recall f1-score support\n",
"\n",
" positive 0.86 0.41 0.56 24864\n",
" negative 0.86 0.98 0.91 88827\n",
"\n",
"avg / total 0.86 0.86 0.84 113691\n",
"\n"
]
}
],
"source": [
"# Print the values precision , recall and F1-score for Naive Bayes classification\n",
"from sklearn.metrics import confusion_matrix\n",
"from sklearn import metrics\n",
"from sklearn.metrics import roc_curve, auc,roc_auc_score\n",
"print(\"The classification metric values for Bernoulli naive bayes classification are \")\n",
"print(metrics.classification_report(y_test, prediction['Bernoulli'], target_names = [\"positive\", \"negative\"]))\n"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"_cell_guid": "2f34be1c-1d8f-4990-a758-56e867f694ef",
"_uuid": "a77e9ef619a3217c21ba27ed00d109ccbf58fae5"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The connfusion matrix for Bernoulli NB \n",
"[[10210 14654]\n",
" [ 1676 87151]]\n"
]
}
],
"source": [
"print(\"The connfusion matrix for Bernoulli NB \")\n",
"print(confusion_matrix(y_test,prediction['Bernoulli']))"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "afabe9a5-ca30-4208-be85-e55563b83be1",
"_uuid": "9f5d6239646c950820c56fade71d4eda6a4a57ba"
},
"source": [
"\n",
"**Task - 4** ( Logistic regression on the train data on tf_idf vectorized text summarisation )"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"_cell_guid": "e1ced79c-baac-43a5-9072-29f2085ab200",
"_uuid": "e548f5ed6c6c902b81c61573e21391b934e21f2d",
"collapsed": true
},
"outputs": [],
"source": [
"from sklearn.linear_model import LogisticRegression\n",
"logreg = LogisticRegression(C=1e6)\n",
"logreg_result = logreg.fit(X_train_tfidf, y_train)\n",
"prediction['Logistic'] = logreg.predict(X_test_tfidf)"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"_cell_guid": "f51e3d74-a141-41d0-bb94-66fd48cd6681",
"_uuid": "b18898a3ec171e26c18e812b1bf0d7c049799191"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The classification metric values for Logistic regression are \n",
" precision recall f1-score support\n",
"\n",
" positive 0.87 0.83 0.85 24864\n",
" negative 0.95 0.96 0.96 88827\n",
"\n",
"avg / total 0.93 0.93 0.93 113691\n",
"\n"
]
}
],
"source": [
"# Print the values precision , recall and F1-score for Logistic regression\n",
"from sklearn.metrics import confusion_matrix\n",
"from sklearn import metrics\n",
"from sklearn.metrics import roc_curve, auc\n",
"print(\"The classification metric values for Logistic regression are \")\n",
"print(metrics.classification_report(y_test, prediction['Logistic'], target_names = [\"positive\", \"negative\"]))"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"_cell_guid": "7453de6a-4471-4077-b543-ff4a0ec24fa0",
"_uuid": "2acd123214d01899031837642cee301d410adf06"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The connfusion matrix for Bernoulli NB \n",
"[[20518 4346]\n",
" [ 3174 85653]]\n"
]
}
],
"source": [
"print(\"The connfusion matrix for Bernoulli NB \")\n",
"print(confusion_matrix(y_test,prediction['Logistic']))\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "745661e1-978d-47a6-af6d-b4521af769a4",
"_uuid": "7f35fb0944de9de5f8b94b47cec6de9597f55cd9"
},
"source": [
"**Task - 5** ( Apply LinearSVM and RBF-SVM on the given train data )"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"_cell_guid": "169bb468-13c7-41a1-9a71-93da11d2b75c",
"_uuid": "411126c54bbf52dae933d24fe7301f6e006c84de",
"collapsed": true
},
"outputs": [],
"source": [
"from sklearn.svm import LinearSVC\n",
"resultSVC = LinearSVC( max_iter=1000)\n",
"resultSVCClassifier = resultSVC.fit(X_train_tfidf , y_train)\n",
"prediction['LinearSVC'] = resultSVC.predict(X_test_tfidf)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"_cell_guid": "c8d2d44b-4832-4035-b3a1-16a3c541b385",
"_uuid": "bfb6d06537d7cecaedcdb46bd120b7b6f74790e4"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The classification metric values for linear SVM classification are \n"
]
}
],
"source": [
"# Print the values precision , recall and F1-score for Linear SVC\n",
"from sklearn.metrics import confusion_matrix\n",
"from sklearn import metrics\n",
"from sklearn.metrics import roc_curve, auc\n",
"print(\"The classification metric values for linear SVM classification are \")\n",
"print(metrics.classification_report(y_test, prediction['LinearSVC'], target_names = [\"positive\", \"negative\"]))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"_cell_guid": "43a7bf30-7bce-415f-96cf-8dde77a13a62",
"_uuid": "8a3e9c7eaaa1fe785518b39521f36beb7cc1e71d",
"collapsed": true
},
"outputs": [],
"source": [
"print(\"The connfusion matrix for Bernoulli NB \")\n",
"print(confusion_matrix(y_test,prediction['']))\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"_cell_guid": "8fabf565-2f43-469b-a7b8-22c44bc507ea",
"_uuid": "b403a2d8ec40582ae2c4533148fee40f80c69c40",
"collapsed": true
},
"outputs": [],
"source": [
"from sklearn.svm import SVC\n",
"resultSVC = SVC(kernel='rbf')\n",
"resultSVCClassifier = resultSVC.fit(X_train_tfidf , y_train)\n",
"prediction['rbfSVC'] = resultSVC.predict(X_test_tfidf )"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"_cell_guid": "71ea4e8f-4604-48c3-85b5-52c866b72486",
"_uuid": "744d2192df2e099e88fdbdb7da52ab9d19342041",
"collapsed": true
},
"outputs": [],
"source": [
"# Print the values precision , recall and F1-score for RBF SVC\n",
"from sklearn.metrics import confusion_matrix\n",
"from sklearn import metrics\n",
"from sklearn.metrics import roc_curve, auc\n",
"print(\"The classification metric values for RBF SVM classification are \")\n",
"print(metrics.classification_report(y_test, prediction['rbfSVC'], target_names = [\"positive\", \"negative\"]))"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.1"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
| 0001/480/1480191.ipynb | s3://data-agents/kaggle-outputs/sharded/034_00001.jsonl.gz |
{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "9a45f08b-c554-1b35-a50d-c64150d6f789",
"_uuid": "243417671eb522fdf34fb3f85b9fa90c2223080a"
},
"source": [
"This notebook is forked from : https://www.kaggle.com/sudalairajkumar/simple-exploration-notebook-instacart/notebook\n",
"\n",
"In this notebook, we will try and explore the basic information about the dataset given. The dataset for this competition is a relational set of files describing customers' orders over time. \n",
"\n",
"**Objective:** \n",
"\n",
"The goal of the competition is to predict which products will be in a user's next order. The dataset is anonymized and contains a sample of over 3 million grocery orders from more than 200,000 Instacart users.\n",
"\n",
"For each user, 4 and 100 of their orders are given, with the sequence of products purchased in each order\n",
"\n",
"Let us start by importing the necessary modules."
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "59b82242-0d3e-4875-add7-732b94631570",
"_uuid": "786711e429bbc9b3a9b79a65bcd60d946e34ad28"
},
"source": [
"## Import modules"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"_cell_guid": "4c76ddb9-4f12-d6d2-56aa-82c3254de71a",
"_uuid": "12c586c92f221f56ffda59830ecf0e94c6d290bd",
"collapsed": true
},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"color = sns.color_palette()\n",
"\n",
"%matplotlib inline"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "96355f94-3cd7-f536-0cf2-dfde8441a46a",
"_uuid": "84fa2382de87bdbbb44dd0471655239dcddc7c18"
},
"source": [
"Let us list out the files that are present in this competition.!"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"_cell_guid": "45ad0ba2-2d31-e90d-4e10-83fd3247a859",
"_uuid": "11aed9509e20bd5bcf5160fc3f28234f2193f040"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"aisles.csv\n",
"departments.csv\n",
"order_products__prior.csv\n",
"order_products__train.csv\n",
"orders.csv\n",
"products.csv\n",
"sample_submission.csv\n",
"\n"
]
}
],
"source": [
"from subprocess import check_output\n",
"print(check_output([\"ls\", \"../input\"]).decode(\"utf8\"))"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "1a44f145-b654-7b37-9528-bcf1a62a6071",
"_uuid": "e5cd2713fe2b6cc2712638cda4a9918d01faeb5a"
},
"source": [
"Before we dive deep into the exploratory analysis, let us know a little more about the files given. To understand it better, let us first read all the files as dataframe objects and then look at the top few rows.\n",
"\n",
"## Import data"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"_cell_guid": "28175438-a8f6-410d-9d8f-60eaefe1152d",
"_uuid": "608a18abda91b7dd01116623fdd4966cc801b5aa",
"collapsed": true
},
"outputs": [],
"source": [
"order_products_train_df = pd.read_csv(\"../input/order_products__train.csv\")\n",
"order_products_prior_df = pd.read_csv(\"../input/order_products__prior.csv\")\n",
"orders_df = pd.read_csv(\"../input/orders.csv\")\n",
"products_df = pd.read_csv(\"../input/products.csv\")\n",
"aisles_df = pd.read_csv(\"../input/aisles.csv\")\n",
"departments_df = pd.read_csv(\"../input/departments.csv\")"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"_cell_guid": "398b93eb-873e-728e-be4c-e101adb9d26d",
"_uuid": "93541ee6583416594b86bfb8a5b6b5c41f008663"
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>order_id</th>\n",
" <th>user_id</th>\n",
" <th>eval_set</th>\n",
" <th>order_number</th>\n",
" <th>order_dow</th>\n",
" <th>order_hour_of_day</th>\n",
" <th>days_since_prior_order</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2539329</td>\n",
" <td>1</td>\n",
" <td>prior</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>8</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2398795</td>\n",
" <td>1</td>\n",
" <td>prior</td>\n",
" <td>2</td>\n",
" <td>3</td>\n",
" <td>7</td>\n",
" <td>15.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>473747</td>\n",
" <td>1</td>\n",
" <td>prior</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>12</td>\n",
" <td>21.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2254736</td>\n",
" <td>1</td>\n",
" <td>prior</td>\n",
" <td>4</td>\n",
" <td>4</td>\n",
" <td>7</td>\n",
" <td>29.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>431534</td>\n",
" <td>1</td>\n",
" <td>prior</td>\n",
" <td>5</td>\n",
" <td>4</td>\n",
" <td>15</td>\n",
" <td>28.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" order_id user_id eval_set order_number order_dow order_hour_of_day \\\n",
"0 2539329 1 prior 1 2 8 \n",
"1 2398795 1 prior 2 3 7 \n",
"2 473747 1 prior 3 3 12 \n",
"3 2254736 1 prior 4 4 7 \n",
"4 431534 1 prior 5 4 15 \n",
"\n",
" days_since_prior_order \n",
"0 NaN \n",
"1 15.0 \n",
"2 21.0 \n",
"3 29.0 \n",
"4 28.0 "
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"orders_df.head()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"_cell_guid": "07b7e152-8de3-3a18-d286-7158cba15e5d",
"_uuid": "3cac6744a7d95493451223213f3f0ae993f65cee"
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>order_id</th>\n",
" <th>product_id</th>\n",
" <th>add_to_cart_order</th>\n",
" <th>reordered</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1</td>\n",
" <td>49302</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>1</td>\n",
" <td>11109</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>1</td>\n",
" <td>10246</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>1</td>\n",
" <td>49683</td>\n",
" <td>4</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>1</td>\n",
" <td>43633</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" order_id product_id add_to_cart_order reordered\n",
"0 1 49302 1 1\n",
"1 1 11109 2 1\n",
"2 1 10246 3 0\n",
"3 1 49683 4 0\n",
"4 1 43633 5 1"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"order_products_train_df.head()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"_cell_guid": "0db75f9d-fa7d-65b6-4527-65830b84cb50",
"_uuid": "0f9a090702285763801a88263f91285b13343481"
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>order_id</th>\n",
" <th>product_id</th>\n",
" <th>add_to_cart_order</th>\n",
" <th>reordered</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2</td>\n",
" <td>33120</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2</td>\n",
" <td>28985</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2</td>\n",
" <td>9327</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2</td>\n",
" <td>45918</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2</td>\n",
" <td>30035</td>\n",
" <td>5</td>\n",
" <td>0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" order_id product_id add_to_cart_order reordered\n",
"0 2 33120 1 1\n",
"1 2 28985 2 1\n",
"2 2 9327 3 0\n",
"3 2 45918 4 1\n",
"4 2 30035 5 0"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"order_products_prior_df.head()"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "9ce2a903-52ba-d57b-401c-9ed9b3d5269a",
"_uuid": "821363a35c077219a4e7c369f61b18e4ba9edaf0"
},
"source": [
"As we could see, orders.csv has all the information about the given order id like the user who has purchased the order, when was it purchased, days since prior order and so on.\n",
"\n",
"The columns present in order_products_train and order_products_prior are same. Then what is the difference between these files.?\n",
"\n",
"As mentioned earlier, in this dataset, 4 to 100 orders of a customer are given (we will look at this later) and we need to predict the products that will be re-ordered. So the last order of the user has been taken out and divided into train and test sets. All the prior order informations of the customer are present in order_products_prior file. We can also note that there is a column in orders.csv file called eval_set which tells us as to which of the three datasets (prior, train or test) the given row goes to.\n",
"\n",
"Order_products*csv file has more detailed information about the products that been bought in the given order along with the re-ordered status.\n",
"\n",
"Let us first get the count of rows in each of the three sets."
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"_cell_guid": "71019383-4ad9-62c3-9f9a-d0d5bb326f99",
"_uuid": "cd2dae2c3e640a8d98ca2473cb9e74febd3888d7"
},
"outputs": [
{
"data": {
"image/png": 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AiLgOmArsApxb+swGzo6IccCWmXlTab+EJthvAvwgM58AuiPiLmDrMsZhLX0vHbrLkyRJ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\n/wM6TJ3kUT7vjgAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f1a403f84a8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"cnt_srs = orders_df.eval_set.value_counts()\n",
"\n",
"plt.figure(figsize=(12,8))\n",
"sns.barplot(cnt_srs.index, cnt_srs.values, alpha=0.8, color=color[1])\n",
"plt.ylabel(\"# Occurences\")\n",
"plt.xlabel(\"eval_set type\")\n",
"plt.title(\"Count of rows in each dataset\")\n",
"plt.xticks(rotation=45)\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"_cell_guid": "4631d5bd-54e4-5057-e3d6-de53f924c5e4",
"_uuid": "7fb89ed887dfabdc9b8b9d15147ae04ee05c092b"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"eval_set\n",
"prior 206209\n",
"test 75000\n",
"train 131209\n",
"Name: user_id, dtype: int64\n"
]
}
],
"source": [
"def get_unique_count(x):\n",
" return len(np.unique(x))\n",
"\n",
"cnt_srs = orders_df.groupby(\"eval_set\")[\"user_id\"].aggregate(get_unique_count)\n",
"print(cnt_srs)"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "2a2dc58e-7df6-f42d-8b42-e94e2ece30a2",
"_uuid": "9eaa4fcfcc7eaa8e774e917c8226fa71f810f6df"
},
"source": [
"So there are 206,209 customers in total. Out of which, the last purchase of 131,209 customers are given as train set and we need to predict for the rest 75,000 customers. \n",
"\n",
"Now let us validate the claim that 4 to 100 orders of a customer are given. "
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"_cell_guid": "ccddb4a4-1fb7-f1b1-fbaf-80a2d5814522",
"_uuid": "68359750453090edc6980630821996de2e6473ca"
},
"outputs": [
{
"data": {
"image/png": 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hhnFJkiSpIYZxSZIkqSGGcUmSJKkhwzu58IhYDfgVcEJmnhgRZwBrAk/VWY7LzIsjYkdg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\n/wfR974rHWhZOQAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f1a403e8cf8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"cnt_srs = orders_df.groupby(\"user_id\")[\"order_number\"].aggregate(np.max)\n",
"cnt_srs = cnt_srs.reset_index()\n",
"cnt_srs = cnt_srs.order_number.value_counts()\n",
"\n",
"plt.figure(figsize=(12,8))\n",
"sns.barplot(cnt_srs.index, cnt_srs.values, alpha=0.8)\n",
"plt.ylabel(\"# occurences\")\n",
"plt.xlabel(\"Maximum order number\")\n",
"plt.title(\"# Max order number\")\n",
"plt.xticks(rotation=45)\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "e2180926-1db1-aca7-1257-5906d92d24f0",
"_uuid": "4ede83351c55fc944260ecc2f9a36aef009013f5"
},
"source": [
"So there are no orders less than 4 and is max capped at 100 as given in the data page. \n",
"\n",
"Now let us see how the ordering habit changes with day of week."
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"_cell_guid": "fd013d90-47b5-aa52-fbe4-e86e1f568fb2",
"_uuid": "70e161c9d0ed4fdae1e426a6f6a91264be4dc67c"
},
"outputs": [
{
"data": {
"image/png": 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/JEmbjrYF8cz8DXBpefuLiPgtsFtEbFGWoEwFlpSvKS2HTgVua2n/cblxs4vmBs9J/fbt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\ngg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f1a3cf80eb8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(12,8))\n",
"sns.countplot(x=\"order_dow\", data=orders_df, color=color[0])\n",
"plt.ylabel(\"Count\")\n",
"plt.xlabel(\"Day of week\")\n",
"plt.title(\"Frequency of order by week day\")\n",
"plt.xticks(rotation=45)\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "c84085f7-f485-bc58-ffff-8794e5e0dc50",
"_uuid": "b9e55b980df3a9108e5538f292badc1db7ab946d"
},
"source": [
"Seems like 0 and 1 is Saturday and Sunday when the orders are high and low during Wednesday.\n",
"\n",
"Now we shall see how the distribution is with respect to time of the day."
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"_cell_guid": "d5a3cc83-fa06-5657-41c7-46bdbb7f8a72",
"_uuid": "8a508e332438177d877c95bdb0114f8cfc6c5b0c"
},
"outputs": [
{
"data": {
"image/png": 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SSAP0kvToTJu2rvWsZ70B15LGg64P1nwR8HbgxZm5ALim5+7LKQddXkIZ6R6yOXADcHtd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\nALyVOY+EKvD7AAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f1a39fd6a58>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(12,8))\n",
"sns.countplot(x=\"order_hour_of_day\", data=orders_df, color=color[1])\n",
"plt.ylabel(\"# occurences\")\n",
"plt.xlabel(\"Hour of day\")\n",
"plt.title(\"Frequencies of order by hour of day\")\n",
"plt.xticks(rotation=45)\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "ed48981b-dba9-f695-28ca-416f61f7594e",
"_uuid": "d55cbfde07f26e792578ca35e38279dafb111e80"
},
"source": [
"So majority of the orders are made during day time. Now let us combine the day of week and hour of day to see the distribution."
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"_cell_guid": "c8252648-05a3-959f-3e4e-03a3b01012fa",
"_uuid": "55f80c09d756f1830301d7ed06512625b9533662"
},
"outputs": [
{
"data": {
"image/png": 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NG8/2MV+cyackSVJBk7XOZ2beDpxa3705Iv4AbBkR8+ru9Q2AO+qfBW1P3QC4qm37z+vJ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\nQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f1a3d05d550>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"grouped_df = orders_df.groupby([\"order_dow\", \"order_hour_of_day\"])[\"order_number\"]\\\n",
" .aggregate(\"count\").reset_index()\n",
"grouped_df = grouped_df.pivot(\"order_dow\", \"order_hour_of_day\", \"order_number\")\n",
"\n",
"plt.figure(figsize=(12,8))\n",
"sns.heatmap(grouped_df)\n",
"plt.title(\"Frequency of day_of_week VS hour_of_day\")\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "7c70b0de-247b-d415-8b75-a8578461ec91",
"_uuid": "63b5374caffe46d550b7883142fb9850aeb4f79f"
},
"source": [
"Seems Satuday evenings and Sunday mornings are the prime time for orders.\n",
"\n",
"Now let us check the time interval between the orders."
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"_cell_guid": "2845917a-0999-c9a1-94f2-c2c8e45fbf03",
"_uuid": "f59f1e53d12c9858a4fbe739bce809f78029c856"
},
"outputs": [
{
"data": {
"image/png": 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JUgUGcUmSJKkCg7gkSZJUgUFckiRJqsAgLkmSJFVgEJckSZIqMIhLkiRJFRjE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\nAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f1a39d85a20>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(12,8))\n",
"sns.countplot(x=\"days_since_prior_order\", data=orders_df, color=color[3])\n",
"plt.ylabel(\"#\")\n",
"plt.xlabel(\"days_since_prior_order\")\n",
"plt.title(\"Frequency by days_since_prior_order\")\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "7edf3a56-1dd0-d0b3-3057-a0eafc57a8ac",
"_uuid": "24b66b2e57b9269d5f04a2cb9e3ca4f36607185a"
},
"source": [
"Looks like customers order once in every week (check the peak at 7 days) or once in a month (peak at 30 days). We could also see smaller peaks at 14, 21 and 28 days (weekly intervals).\n",
"\n",
"Since our objective is to figure out the re-orders, let us check out the re-order percentage in prior set and train set."
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"_cell_guid": "371aeeb5-ae2e-a917-a872-90ef56e063c9",
"_uuid": "ea415e5e919b05745cf51bad107702b6c3492969"
},
"outputs": [
{
"data": {
"text/plain": [
"0.5896974667922161"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"order_products_prior_df[\"reordered\"].sum() / order_products_prior_df.shape[0]\n"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"_cell_guid": "5b2b567e-073a-d9e4-1b64-9ae66ba65188",
"_uuid": "c60d236574c00cbfcc378fc8590ce8e91dcad8a8"
},
"outputs": [
{
"data": {
"text/plain": [
"0.5985944127509629"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"order_products_train_df[\"reordered\"].sum() / order_products_train_df.shape[0]\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "bebb053d-7868-27b2-e57c-0997af22cec8",
"_uuid": "aeb3dead93fddd68314a26b7be5be0b05950738c"
},
"source": [
"On an average, about 59% of the products in an order are re-ordered products.\n",
"\n",
"**No re-ordered products:**\n",
"\n",
"Now that we have seen 59% of the products are re-ordered, there will also be situations when none of the products are re-ordered. Let us check that now."
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"_cell_guid": "f3182fcd-77bb-c1e0-a93f-437674bd282a",
"_uuid": "258fb97f0fe9c5482c2ae413b2ba08b425971815"
},
"outputs": [
{
"data": {
"text/plain": [
"1 0.879151\n",
"0 0.120849\n",
"Name: reordered, dtype: float64"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"def no_re_ordered_products_rate(df):\n",
" grouped_df = df.groupby(\"order_id\")[\"reordered\"].aggregate(\"sum\").reset_index()\n",
" grouped_df[\"reordered\"].loc[grouped_df[\"reordered\"]>1] = 1\n",
" return grouped_df.reordered.value_counts() / grouped_df.shape[0]\n",
"\n",
"no_re_ordered_products_rate(order_products_prior_df)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"_cell_guid": "d80b43f0-1139-5ed4-475d-c6bd9c144711",
"_uuid": "0e30e3d247476222e4022d5511662d8e3b025130"
},
"outputs": [
{
"data": {
"text/plain": [
"1 0.93444\n",
"0 0.06556\n",
"Name: reordered, dtype: float64"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"no_re_ordered_products_rate(order_products_train_df)"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "577ca5cd-0222-9f42-d3be-8704d8085d96",
"_uuid": "d65b2b86508abc76ac25fabf967c2d5d7da63710"
},
"source": [
"About 12% of the orders in prior set has no re-ordered items while in the train set it is 6.5%.\n",
"\n",
"Now let us see the number of products bought in each order."
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"_cell_guid": "5f008745-1fa5-96c9-3586-f333689ce032",
"_uuid": "db0d1129dc0758db29b1b043bf330c6577706e76"
},
"outputs": [
{
"data": {
"image/png": 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0p4w8BzszfxcRp2fmvwNExF8Cr6e5o6MkSZKkwkxuNPPvnZ+f2v54ydgykiRJkuawaa+D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\nliRJkir6/wH0hgiyLgD6rwAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f1a39ba7780>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"grouped_df = order_products_train_df.groupby(\"order_id\")[\"add_to_cart_order\"].aggregate(\"max\").reset_index()\n",
"cnt_srs = grouped_df[\"add_to_cart_order\"].value_counts()\n",
"\n",
"plt.figure(figsize=(12,8))\n",
"sns.barplot(cnt_srs.index, cnt_srs.values, alpha=0.8)\n",
"plt.ylabel(\"# Count\")\n",
"plt.xlabel(\"# of products in the given order\")\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "e04654e3-c4ec-8711-140c-4fad41f421df",
"_uuid": "f2d8f35f1f180885e388db92450f02806fc55d47"
},
"source": [
"A right tailed distribution with the maximum value at 5.!\n",
"\n",
"Before we explore the product details, let us look at the other three files as well. "
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"_cell_guid": "c5a01d40-d6e8-efb6-6559-0fc5f674ddb6",
"_uuid": "3228878d1c9a1fa69583f3a89026208c69805677"
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>product_id</th>\n",
" <th>product_name</th>\n",
" <th>aisle_id</th>\n",
" <th>department_id</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1</td>\n",
" <td>Chocolate Sandwich Cookies</td>\n",
" <td>61</td>\n",
" <td>19</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2</td>\n",
" <td>All-Seasons Salt</td>\n",
" <td>104</td>\n",
" <td>13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>3</td>\n",
" <td>Robust Golden Unsweetened Oolong Tea</td>\n",
" <td>94</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>4</td>\n",
" <td>Smart Ones Classic Favorites Mini Rigatoni Wit...</td>\n",
" <td>38</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>5</td>\n",
" <td>Green Chile Anytime Sauce</td>\n",
" <td>5</td>\n",
" <td>13</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" product_id product_name aisle_id \\\n",
"0 1 Chocolate Sandwich Cookies 61 \n",
"1 2 All-Seasons Salt 104 \n",
"2 3 Robust Golden Unsweetened Oolong Tea 94 \n",
"3 4 Smart Ones Classic Favorites Mini Rigatoni Wit... 38 \n",
"4 5 Green Chile Anytime Sauce 5 \n",
"\n",
" department_id \n",
"0 19 \n",
"1 13 \n",
"2 7 \n",
"3 1 \n",
"4 13 "
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"products_df.head()"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"_cell_guid": "c48ba63b-117c-1900-2b4d-24d5a5442e71",
"_uuid": "bd0d9568a886a8173d04568d4520c8a2e1da6145"
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>aisle_id</th>\n",
" <th>aisle</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1</td>\n",
" <td>prepared soups salads</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2</td>\n",
" <td>specialty cheeses</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>3</td>\n",
" <td>energy granola bars</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>4</td>\n",
" <td>instant foods</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>5</td>\n",
" <td>marinades meat preparation</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" aisle_id aisle\n",
"0 1 prepared soups salads\n",
"1 2 specialty cheeses\n",
"2 3 energy granola bars\n",
"3 4 instant foods\n",
"4 5 marinades meat preparation"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"aisles_df.head()"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"_cell_guid": "69cf5c8f-1c10-5731-6a68-3a8141442ae4",
"_uuid": "c56e833ffd8827c432a7e71efe2d06baac7ad748"
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>department_id</th>\n",
" <th>department</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1</td>\n",
" <td>frozen</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2</td>\n",
" <td>other</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>3</td>\n",
" <td>bakery</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>4</td>\n",
" <td>produce</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>5</td>\n",
" <td>alcohol</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" department_id department\n",
"0 1 frozen\n",
"1 2 other\n",
"2 3 bakery\n",
"3 4 produce\n",
"4 5 alcohol"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"departments_df.head()"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "8898f07d-f6cb-227b-6a03-11cf857b035f",
"_uuid": "d9891354179b9ae0795e47f0f4fb0b2d2288f550"
},
"source": [
"Now let us merge these product details with the order_prior details."
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"_cell_guid": "a8973ae6-4f89-b4b7-18fe-a722fea7c470",
"_uuid": "afbda9d68862117c5cdeec281ba09ed4bed3da1f"
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>order_id</th>\n",
" <th>product_id</th>\n",
" <th>add_to_cart_order</th>\n",
" <th>reordered</th>\n",
" <th>product_name</th>\n",
" <th>aisle_id</th>\n",
" <th>department_id</th>\n",
" <th>aisle</th>\n",
" <th>department</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2</td>\n",
" <td>33120</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>Organic Egg Whites</td>\n",
" <td>86</td>\n",
" <td>16</td>\n",
" <td>eggs</td>\n",
" <td>dairy eggs</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2</td>\n",
" <td>28985</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>Michigan Organic Kale</td>\n",
" <td>83</td>\n",
" <td>4</td>\n",
" <td>fresh vegetables</td>\n",
" <td>produce</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2</td>\n",
" <td>9327</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>Garlic Powder</td>\n",
" <td>104</td>\n",
" <td>13</td>\n",
" <td>spices seasonings</td>\n",
" <td>pantry</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2</td>\n",
" <td>45918</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>Coconut Butter</td>\n",
" <td>19</td>\n",
" <td>13</td>\n",
" <td>oils vinegars</td>\n",
" <td>pantry</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2</td>\n",
" <td>30035</td>\n",
" <td>5</td>\n",
" <td>0</td>\n",
" <td>Natural Sweetener</td>\n",
" <td>17</td>\n",
" <td>13</td>\n",
" <td>baking ingredients</td>\n",
" <td>pantry</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" order_id product_id add_to_cart_order reordered product_name \\\n",
"0 2 33120 1 1 Organic Egg Whites \n",
"1 2 28985 2 1 Michigan Organic Kale \n",
"2 2 9327 3 0 Garlic Powder \n",
"3 2 45918 4 1 Coconut Butter \n",
"4 2 30035 5 0 Natural Sweetener \n",
"\n",
" aisle_id department_id aisle department \n",
"0 86 16 eggs dairy eggs \n",
"1 83 4 fresh vegetables produce \n",
"2 104 13 spices seasonings pantry \n",
"3 19 13 oils vinegars pantry \n",
"4 17 13 baking ingredients pantry "
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"order_products_prior_df = pd.merge(order_products_prior_df, products_df, on='product_id', how='left')\n",
"order_products_prior_df = pd.merge(order_products_prior_df, aisles_df, on='aisle_id', how='left')\n",
"order_products_prior_df = pd.merge(order_products_prior_df, departments_df, on='department_id', how='left')\n",
"order_products_prior_df.head()"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {
"_cell_guid": "6508267f-4e84-d7fc-55e3-108f683dc751",
"_uuid": "91e63bee451e61e04742d318f8d173a307326019"
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>product_name</th>\n",
" <th>frequency_count</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Banana</td>\n",
" <td>472565</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Bag of Organic Bananas</td>\n",
" <td>379450</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Organic Strawberries</td>\n",
" <td>264683</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Organic Baby Spinach</td>\n",
" <td>241921</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Organic Hass Avocado</td>\n",
" <td>213584</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>Organic Avocado</td>\n",
" <td>176815</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>Large Lemon</td>\n",
" <td>152657</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>Strawberries</td>\n",
" <td>142951</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>Limes</td>\n",
" <td>140627</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>Organic Whole Milk</td>\n",
" <td>137905</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>Organic Raspberries</td>\n",
" <td>137057</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>Organic Yellow Onion</td>\n",
" <td>113426</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>Organic Garlic</td>\n",
" <td>109778</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>Organic Zucchini</td>\n",
" <td>104823</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>Organic Blueberries</td>\n",
" <td>100060</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>Cucumber Kirby</td>\n",
" <td>97315</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>Organic Fuji Apple</td>\n",
" <td>89632</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>Organic Lemon</td>\n",
" <td>87746</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>Apple Honeycrisp Organic</td>\n",
" <td>85020</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>Organic Grape Tomatoes</td>\n",
" <td>84255</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" product_name frequency_count\n",
"0 Banana 472565\n",
"1 Bag of Organic Bananas 379450\n",
"2 Organic Strawberries 264683\n",
"3 Organic Baby Spinach 241921\n",
"4 Organic Hass Avocado 213584\n",
"5 Organic Avocado 176815\n",
"6 Large Lemon 152657\n",
"7 Strawberries 142951\n",
"8 Limes 140627\n",
"9 Organic Whole Milk 137905\n",
"10 Organic Raspberries 137057\n",
"11 Organic Yellow Onion 113426\n",
"12 Organic Garlic 109778\n",
"13 Organic Zucchini 104823\n",
"14 Organic Blueberries 100060\n",
"15 Cucumber Kirby 97315\n",
"16 Organic Fuji Apple 89632\n",
"17 Organic Lemon 87746\n",
"18 Apple Honeycrisp Organic 85020\n",
"19 Organic Grape Tomatoes 84255"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"cnt_srs = order_products_prior_df[\"product_name\"].value_counts().reset_index()\n",
"cnt_srs = cnt_srs.head(20)\n",
"cnt_srs.columns = [\"product_name\", \"frequency_count\"]\n",
"cnt_srs"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "b199c4ff-16ad-8e99-f8c4-2e11508b390b",
"_uuid": "576292ecdd9448c28119b7c1e52db3f604b34682"
},
"source": [
"Wow. Most of them are organic products.! Also majority of them are fruits. \n",
"\n",
"Now let us look at the important aisles."
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {
"_cell_guid": "e5d7bdb0-3e66-f8e9-22c8-4cfa8b12b632",
"_uuid": "7ab9f5cc1c792b7e05205e45179381f6b0ad2b8f"
},
"outputs": [
{
"data": {
"image/png": 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XAn+hBPKPNGVXAR8HEpiembMAIuIOYBwwEbigqTsF+E5EjAQ2zMzpLW1sD6wDXJeZzwBd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\nTDd+GgAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f1a39e11860>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"cnt_srs = order_products_prior_df[\"aisle\"].value_counts().head(20)\n",
"plt.figure(figsize=(12,8))\n",
"sns.barplot(cnt_srs.index, cnt_srs.values, alpha=0.8)\n",
"plt.ylabel(\"# count\")\n",
"plt.xlabel(\"Aisle\")\n",
"plt.title(\"Distribution of products by aisle\")\n",
"plt.xticks(rotation=45)\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "f8464fc1-2e14-a879-e6b3-e30f6e59ca9a",
"_uuid": "8a01aa9178190b0233607bee7f3201bb1393d4a3"
},
"source": [
"The top two aisles are fresh fruits and fresh vegetables.! \n",
"\n",
"**Department Distribution:**\n",
"\n",
"Let us now check the department wise distribution."
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {
"_cell_guid": "26c6b059-5b6e-ad21-588c-cc12fd59dade",
"_uuid": "78920927949b89e9844e621f94a0479670db7fa6"
},
"outputs": [
{
"data": {
"image/png": 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ihU9hVZ1rdQUww6BrwthVVRhBb2vbOq1y3+mwr2jmBD+eqH/vw2XHruHJTscQ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\nCQqwYDPa2SQAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f1a39c25c18>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"temp_series = order_products_prior_df[\"department\"].value_counts()\n",
"plt.figure(figsize=(8,8))\n",
"labels = (np.array(temp_series.index))\n",
"sizes = (np.array((temp_series/temp_series.sum())*100))\n",
"\n",
"plt.pie(sizes, labels=labels, autopct=\"%1.1f%%\", startangle=200)\n",
"plt.title(\"Distribution of products by department\")\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "e3ba7ecb-a613-95eb-369b-c8fd0e0b54e0",
"_uuid": "6361e13afb194bde6fec609b0863c025a7efd412"
},
"source": [
"Produce is the largest department. Now let us check the reordered percentage of each department. \n",
"\n",
"**Department wise reorder ratio:**"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {
"_cell_guid": "c16f74ef-6649-3125-457f-e0cdbf6683d1",
"_uuid": "d5fd32663b13c8c5f72e153b359b5f78f5f2c610"
},
"outputs": [
{
"data": {
"image/png": 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1kUDHhvu1tatpJiovucy6gCZBURT4luumfXB8Xt4ztFjYbHCmq8Umqrz4UtjK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8zNxpg/KKJKfRLw98B3rbX/DrwDeFdYSbUx5qzxv7O8LcCN1tqPAV/DffF/q6lQ+4fnueAduL+H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\nTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f1a39b9bb38>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"grouped_df = order_products_prior_df.groupby([\"department\"])[\"reordered\"].aggregate(\"mean\").reset_index()\n",
"\n",
"plt.figure(figsize=(12,8))\n",
"sns.pointplot(grouped_df[\"department\"].values, grouped_df[\"reordered\"].values, alpha=0.8, color=color[2])\n",
"plt.ylabel(\"Reordered %\")\n",
"plt.xlabel(\"Department\")\n",
"plt.title(\"Reordered ratio by department\")\n",
"plt.xticks(rotation=45)\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "5f683942-23a8-cd48-f29e-1fa81329990d",
"_uuid": "5c21b4777fb80ed9bfdeaaa33bcca273d86ccdb6"
},
"source": [
"Personal care has lowest reorder ratio and dairy eggs have highest reorder ratio.\n",
"\n",
"**Aisle - Reorder ratio:**"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {
"_cell_guid": "4b7e41e6-4363-b719-f61f-aa15659cb163",
"_uuid": "871046440d03324491f47f0db22dbc8b991e8be4"
},
"outputs": [
{
"data": {
"image/png": 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quzZgRONRTG76AMvDl/LGxPfRVYzCy8UJW2uZyUMIIcS/SwK1EKJGMhqNaDQaDEY9JzKO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V8itTQFuUSOjcyWHy4sJKUkmbbuHfi805e08+hQL3HB1QJ/+ompzOwyl/O5Z5l/bi4O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zj7ynuTf5NflkVKZzrTiaqvoKdHod25O2kFmZwcoBq5GKpay8toxBnkPo5BiCpeKPG600vtpO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\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l4HX42Pjecp66LLfSoSl2Cntii68x0HcwE0Im8X2vH7lSeJnS2lKuF11lf+oe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\nFNRCCCGEEEJUw/8BemVeRsbmlccAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f1a3cdb7f98>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"grouped_df = order_products_prior_df.groupby([\"department_id\", \"aisle\"])[\"reordered\"]\\\n",
" .aggregate(\"mean\").reset_index()\n",
"\n",
"fig, ax = plt.subplots(figsize=(12,20))\n",
"ax.scatter(grouped_df.reordered.values, grouped_df.department_id.values)\n",
"for i, txt in enumerate(grouped_df.aisle.values):\n",
" ax.annotate(txt, (grouped_df.reordered.values[i], grouped_df.department_id.values[i]), \\\n",
" rotation=45, ha=\"center\", va=\"center\", color=\"green\")\n",
"\n",
"\n",
"plt.xlabel(\"Reorder ratio\")\n",
"plt.ylabel(\"department_id\")\n",
"plt.title(\"Reorder ratio by aisle and department\")\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "c529f57f-3bd0-6b42-b8b1-d306ba1671ee",
"_uuid": "d0a3a1ab13b0958e1d7c922144c50f13d1cee331"
},
"source": [
"**Add to Cart - Reorder ratio:**\n",
"\n",
"Let us now explore the relationship between how order of adding the product to the cart affects the reorder ratio."
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {
"_cell_guid": "7ff1b0bb-1571-3a4d-ce2a-37ee8d2de0f4",
"_uuid": "2bec82fe0813e7e71823924d7209fb99cb644a22"
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py:179: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
" self._setitem_with_indexer(indexer, value)\n"
]
},
{
"data": {
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PqZFULeliAmuM2ZpGz+TrMycuMQQEAAAAkxK6+Isx5suSdksKSPq8pG2S+q21jxtj1kj6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"text/plain": [
"<matplotlib.figure.Figure at 0x7f1a40421dd8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"order_products_prior_df[\"add_to_cart_order_mod\"] = order_products_prior_df[\"add_to_cart_order\"]\\\n",
" .copy()\n",
"order_products_prior_df[\"add_to_cart_order_mod\"].loc[\\\n",
" order_products_prior_df[\"add_to_cart_order_mod\"] >70] = 70\n",
"grouped_df = order_products_prior_df.groupby([\"add_to_cart_order_mod\"])[\"reordered\"].aggregate(\"mean\").reset_index()\n",
"\n",
"plt.figure(figsize=(12,8))\n",
"sns.pointplot(grouped_df.add_to_cart_order_mod.values, grouped_df.reordered.values, alpha=0.8, color=color[3]) \n",
"plt.ylabel(\"Reorder ratio\")\n",
"plt.xlabel(\"add_to_cart\")\n",
"plt.title(\"Reorder ratio by add_to_cart\")\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "7be627bf-2847-13c4-fbbe-f7f5f43f6068",
"_uuid": "5784c378581cb6c2f3fec9da40dd9772c00a62bf"
},
"source": [
"**Looks like the products that are added to the cart initially are more likely to be reordered again compared to the ones added later.** This makes sense to me as well since we tend to first order all the products we used to buy frequently and then look out for the new products available. \n",
"\n",
"**Reorder ratio by Time based variables:**"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {
"_cell_guid": "f40cb0e9-7aad-e556-8c40-1ccf387c7a34",
"_uuid": "41401f976e6f2cbdd2a8d6927577c9eb91fea061"
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {
"_cell_guid": "6dfdc0e5-3259-e83b-5015-33a8d35e9968",
"_uuid": "0cebe5b1e4266bc70be045fa0ca82a88e2cd8bd4"
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {
"_cell_guid": "683ac606-fd17-fcd6-1b77-764c34b15fd0",
"_uuid": "41752cbb055ad72d0a6572d49b82e8439bdb4878"
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "773fa291-3eb3-706a-2c75-25fd3d7906ea",
"_uuid": "ea9ed048deae8ca320bd382b8a98add76b0d6005"
},
"source": [
"Looks like reorder ratios are quite high during the early mornings compared to later half of the day."
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "2e6b9c1b-86e1-1835-e257-c6483bb5ae12",
"_uuid": "29a413aa9c99c375b7b2c2dfb836a20c235654c1"
},
"source": [
"**Hope it helped. Please leave your comments / suggestions.**"
]
}
],
"metadata": {
"_change_revision": 188,
"_is_fork": false,
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.1"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
| 0001/480/1480208.ipynb | s3://data-agents/kaggle-outputs/sharded/034_00001.jsonl.gz |
{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "0780daa2-6a34-4f39-a473-eef95b6dcd2d",
"_uuid": "b7a0dd6744d62787d5dca3c64ab3d7dda88e12db"
},
"source": [
"# Introduction to the notebook\n",
"\n",
"Talk the truth and shit."
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "0c176854-4043-42db-94c7-27a026abeb05",
"_uuid": "2f0a97451f5fbe999ce26fd6ce1037ac658f27c2"
},
"source": [
"### Contents :\n",
"1. Data Loading\n",
" * Loding modules\n",
" * Loding Data\n",
" * Understanding the Data\n",
"2. Data Exploration\n",
"3. Feature Enfineering\n",
"4. Applying Machine Learning\n",
"5. Selecting the best-fitted model\n",
"6. Submitting the file"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## DATA EXPLORATION"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "41db511c-8318-42ce-a8d4-be4891919353",
"_uuid": "7e365aa55e40fdc8350a63f0ef2aa2457f73d21a"
},
"source": [
"## 1. Loading modules"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"_cell_guid": "8bacee99-4eef-427d-897d-bf566fe89367",
"_execution_state": "idle",
"_uuid": "5ca234480fe3ffb724ebf467d9909e7c82dbfd7b"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"genderclassmodel.csv\n",
"gendermodel.csv\n",
"gendermodel.py\n",
"myfirstforest.py\n",
"test.csv\n",
"train.csv\n",
"\n"
]
}
],
"source": [
"# pandas, numpy\n",
"import numpy as np # linear algebra\n",
"import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
"from pandas import Series,DataFrame\n",
"\n",
"# matplotlib, seaborn\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"%matplotlib inline\n",
"\n",
"# machine learning\n",
"from sklearn.linear_model import LogisticRegression\n",
"from sklearn.svm import SVC, LinearSVC\n",
"from sklearn.ensemble import RandomForestClassifier\n",
"from sklearn.neighbors import KNeighborsClassifier\n",
"from sklearn.naive_bayes import GaussianNB\n",
"\n",
"\n",
"from subprocess import check_output\n",
"print(check_output([\"ls\", \"../input\"]).decode(\"utf8\"))\n",
"\n",
"# Any results you write to the current directory are saved as output."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 2. Loading Data"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"_cell_guid": "8bec529e-768d-4d54-99a0-d7fe25a87669",
"_execution_state": "idle",
"_uuid": "067151af5a61007314a3e2368a7268f32660f515",
"collapsed": true
},
"outputs": [],
"source": [
"train = pd.read_csv('../input/train.csv')\n",
"test = pd.read_csv('../input/test.csv')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 3. Understanding Data"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"_cell_guid": "fd977661-c3d4-47c3-9af6-81f551017253",
"_execution_state": "idle",
"_uuid": "81768366c36938dd5f77f2c4a0e32c9e224efc7e"
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>PassengerId</th>\n",
" <th>Survived</th>\n",
" <th>Pclass</th>\n",
" <th>Name</th>\n",
" <th>Sex</th>\n",
" <th>Age</th>\n",
" <th>SibSp</th>\n",
" <th>Parch</th>\n",
" <th>Ticket</th>\n",
" <th>Fare</th>\n",
" <th>Cabin</th>\n",
" <th>Embarked</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>Braund, Mr. Owen Harris</td>\n",
" <td>male</td>\n",
" <td>22.0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>A/5 21171</td>\n",
" <td>7.2500</td>\n",
" <td>NaN</td>\n",
" <td>S</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
" <td>female</td>\n",
" <td>38.0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>PC 17599</td>\n",
" <td>71.2833</td>\n",
" <td>C85</td>\n",
" <td>C</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>Heikkinen, Miss. Laina</td>\n",
" <td>female</td>\n",
" <td>26.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>STON/O2. 3101282</td>\n",
" <td>7.9250</td>\n",
" <td>NaN</td>\n",
" <td>S</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
" <td>female</td>\n",
" <td>35.0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>113803</td>\n",
" <td>53.1000</td>\n",
" <td>C123</td>\n",
" <td>S</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>5</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>Allen, Mr. William Henry</td>\n",
" <td>male</td>\n",
" <td>35.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>373450</td>\n",
" <td>8.0500</td>\n",
" <td>NaN</td>\n",
" <td>S</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" PassengerId Survived Pclass \\\n",
"0 1 0 3 \n",
"1 2 1 1 \n",
"2 3 1 3 \n",
"3 4 1 1 \n",
"4 5 0 3 \n",
"\n",
" Name Sex Age SibSp \\\n",
"0 Braund, Mr. Owen Harris male 22.0 1 \n",
"1 Cumings, Mrs. John Bradley (Florence Briggs Th... female 38.0 1 \n",
"2 Heikkinen, Miss. Laina female 26.0 0 \n",
"3 Futrelle, Mrs. Jacques Heath (Lily May Peel) female 35.0 1 \n",
"4 Allen, Mr. William Henry male 35.0 0 \n",
"\n",
" Parch Ticket Fare Cabin Embarked \n",
"0 0 A/5 21171 7.2500 NaN S \n",
"1 0 PC 17599 71.2833 C85 C \n",
"2 0 STON/O2. 3101282 7.9250 NaN S \n",
"3 0 113803 53.1000 C123 S \n",
"4 0 373450 8.0500 NaN S "
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"train.head()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"_cell_guid": "4c059c3c-7c51-4500-ae18-eee2cb79e5bb",
"_execution_state": "idle",
"_uuid": "afec282316e8f178124bbd5170a5d8c543eb357f",
"scrolled": true
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>PassengerId</th>\n",
" <th>Survived</th>\n",
" <th>Pclass</th>\n",
" <th>Age</th>\n",
" <th>SibSp</th>\n",
" <th>Parch</th>\n",
" <th>Fare</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>891.000000</td>\n",
" <td>891.000000</td>\n",
" <td>891.000000</td>\n",
" <td>714.000000</td>\n",
" <td>891.000000</td>\n",
" <td>891.000000</td>\n",
" <td>891.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>446.000000</td>\n",
" <td>0.383838</td>\n",
" <td>2.308642</td>\n",
" <td>29.699118</td>\n",
" <td>0.523008</td>\n",
" <td>0.381594</td>\n",
" <td>32.204208</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>257.353842</td>\n",
" <td>0.486592</td>\n",
" <td>0.836071</td>\n",
" <td>14.526497</td>\n",
" <td>1.102743</td>\n",
" <td>0.806057</td>\n",
" <td>49.693429</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>1.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1.000000</td>\n",
" <td>0.420000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>223.500000</td>\n",
" <td>0.000000</td>\n",
" <td>2.000000</td>\n",
" <td>20.125000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>7.910400</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>446.000000</td>\n",
" <td>0.000000</td>\n",
" <td>3.000000</td>\n",
" <td>28.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>14.454200</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>668.500000</td>\n",
" <td>1.000000</td>\n",
" <td>3.000000</td>\n",
" <td>38.000000</td>\n",
" <td>1.000000</td>\n",
" <td>0.000000</td>\n",
" <td>31.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>max</th>\n",
" <td>891.000000</td>\n",
" <td>1.000000</td>\n",
" <td>3.000000</td>\n",
" <td>80.000000</td>\n",
" <td>8.000000</td>\n",
" <td>6.000000</td>\n",
" <td>512.329200</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" PassengerId Survived Pclass Age SibSp \\\n",
"count 891.000000 891.000000 891.000000 714.000000 891.000000 \n",
"mean 446.000000 0.383838 2.308642 29.699118 0.523008 \n",
"std 257.353842 0.486592 0.836071 14.526497 1.102743 \n",
"min 1.000000 0.000000 1.000000 0.420000 0.000000 \n",
"25% 223.500000 0.000000 2.000000 20.125000 0.000000 \n",
"50% 446.000000 0.000000 3.000000 28.000000 0.000000 \n",
"75% 668.500000 1.000000 3.000000 38.000000 1.000000 \n",
"max 891.000000 1.000000 3.000000 80.000000 8.000000 \n",
"\n",
" Parch Fare \n",
"count 891.000000 891.000000 \n",
"mean 0.381594 32.204208 \n",
"std 0.806057 49.693429 \n",
"min 0.000000 0.000000 \n",
"25% 0.000000 7.910400 \n",
"50% 0.000000 14.454200 \n",
"75% 0.000000 31.000000 \n",
"max 6.000000 512.329200 "
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"train.describe()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"_cell_guid": "7fb1668d-2b3c-4dfe-be55-c1d294250bff",
"_execution_state": "idle",
"_uuid": "5ef675de65ed327a6fda0b957d6c1ad676eead7f"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 891 entries, 0 to 890\n",
"Data columns (total 12 columns):\n",
"PassengerId 891 non-null int64\n",
"Survived 891 non-null int64\n",
"Pclass 891 non-null int64\n",
"Name 891 non-null object\n",
"Sex 891 non-null object\n",
"Age 714 non-null float64\n",
"SibSp 891 non-null int64\n",
"Parch 891 non-null int64\n",
"Ticket 891 non-null object\n",
"Fare 891 non-null float64\n",
"Cabin 204 non-null object\n",
"Embarked 889 non-null object\n",
"dtypes: float64(2), int64(5), object(5)\n",
"memory usage: 83.6+ KB\n"
]
}
],
"source": [
"train.info()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"null values description"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Name</th>\n",
" <th>Sex</th>\n",
" <th>Ticket</th>\n",
" <th>Cabin</th>\n",
" <th>Embarked</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>891</td>\n",
" <td>891</td>\n",
" <td>891</td>\n",
" <td>204</td>\n",
" <td>889</td>\n",
" </tr>\n",
" <tr>\n",
" <th>unique</th>\n",
" <td>891</td>\n",
" <td>2</td>\n",
" <td>681</td>\n",
" <td>147</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>top</th>\n",
" <td>Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)</td>\n",
" <td>male</td>\n",
" <td>1601</td>\n",
" <td>C23 C25 C27</td>\n",
" <td>S</td>\n",
" </tr>\n",
" <tr>\n",
" <th>freq</th>\n",
" <td>1</td>\n",
" <td>577</td>\n",
" <td>7</td>\n",
" <td>4</td>\n",
" <td>644</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Name Sex Ticket \\\n",
"count 891 891 891 \n",
"unique 891 2 681 \n",
"top Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg) male 1601 \n",
"freq 1 577 7 \n",
"\n",
" Cabin Embarked \n",
"count 204 889 \n",
"unique 147 3 \n",
"top C23 C25 C27 S \n",
"freq 4 644 "
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"train.describe(include=['O'])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Data Exploration"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "08a03689-d829-4918-b8a9-0d3ad936e364",
"_execution_state": "busy",
"_uuid": "2241757c33c4ccfb2091e896681cdab65f197cbe"
},
"source": [
"## Feature Engineering"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"_cell_guid": "e480111a-52e5-4110-b85c-916d9eaf7381",
"_execution_state": "idle",
"_uuid": "8fc514be8a21264777f719e6c707cbde8e193ba5"
},
"outputs": [
{
"data": {
"text/plain": [
"Index(['PassengerId', 'Survived', 'Pclass', 'Name', 'Sex', 'Age', 'SibSp',\n",
" 'Parch', 'Ticket', 'Fare', 'Cabin', 'Embarked'],\n",
" dtype='object')"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"headers = train.dtypes.index\n",
"headers"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Test every column against the survival and lets decide with to drop which to not."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 1. PassengerId\n",
"\n",
"It is the least required feature in the "
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.1"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
| 0001/480/1480244.ipynb | s3://data-agents/kaggle-outputs/sharded/034_00001.jsonl.gz |
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"_cell_guid": "cd79f3c4-8b03-4de6-b353-285decaca71b",
"_uuid": "1bde2c427d514aed51af3c938d258fb0274999a2"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"crypto-markets.csv\n",
"\n"
]
}
],
"source": [
"# This Python 3 environment comes with many helpful analytics libraries installed\n",
"# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n",
"# For example, here's several helpful packages to load in \n",
"\n",
"import numpy as np # linear algebra\n",
"import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"from datetime import datetime\n",
"from dateutil.parser import parse\n",
"\n",
"# Input data files are available in the \"../input/\" directory.\n",
"# For example, running this (by clicking run or pressing Shift+Enter) will list the files in the input directory\n",
"\n",
"from subprocess import check_output\n",
"print(check_output([\"ls\", \"../input\"]).decode(\"utf8\"))\n",
"CryptoMarkets = pd.read_csv('../input/crypto-markets.csv')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Note that date is an ***object type series*** in this dataframe which is not good when we are going to apply multuple time reated operations. "
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"date object\n",
"open float64\n",
"high float64\n",
"low float64\n",
"close float64\n",
"volume int64\n",
"market int64\n",
"coin object\n",
"aud_open float64\n",
"aud_close float64\n",
"variance float64\n",
"dtype: object"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"CryptoMarkets.dtypes"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The data contains a particular date and prices on that date. But this is still not read as a TimeSeries object as the data types are ‘object’ and ‘int’. In order to read the data as a time series, we have to pass special arguments to the read_csv command:\n"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"_cell_guid": "cd9a862d-32a4-4efc-8567-420c29d06644",
"_uuid": "693bb61af7113da21c238f7db8be85702817b76a",
"scrolled": false
},
"outputs": [
{
"data": {
"text/plain": [
"open float64\n",
"high float64\n",
"low float64\n",
"close float64\n",
"volume int64\n",
"market int64\n",
"coin object\n",
"aud_open float64\n",
"aud_close float64\n",
"variance float64\n",
"dtype: object"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dateparse = lambda dates: pd.datetime.strptime(dates, '%Y-%m-%d')\n",
"cm = pd.read_csv('../input/crypto-markets.csv', parse_dates=['date'], index_col='date', date_parser=dateparse)\n",
"cm.dtypes"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can also explicitly convert to datetime using\n",
"**dataframe[columnName] = dataframe.to_datetime[columnName]**\n",
"\n",
"you can read more about it on following link \n",
"\n",
"https://www.analyticsvidhya.com/blog/2016/02/time-series-forecasting-codes-python/\n",
"https://stackoverflow.com/questions/29370057/select-dataframe-rows-between-two-dates"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"dm = pd.read_csv('../input/crypto-markets.csv') \n",
"dm['date'] = pd.to_datetime(dm['date'])"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"_cell_guid": "00b1d516-19fb-4d6c-9e5b-5c436a0f3105",
"_uuid": "91650e76eb7ebbc35b581686dbd10949c7d0a5ee"
},
"outputs": [],
"source": [
"cmopen=cm.iloc[:50,0]\n",
"cmhigh=cm.iloc[:50,1]\n",
"cmlow=cm.iloc[:50,2]\n",
"cmclose=cm.iloc[:50,3]"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"_cell_guid": "3249def2-8235-4051-9644-0be407365dbc",
"_uuid": "994eb52e51ee3197e4fe17cd167368bde276765f"
},
"outputs": [
{
"data": {
"image/png": 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hJJysTuBnDgrUSDtsrd+xDcVsxtbQ87A3QO4N7mjz7549VsHMBn9rCCGEyGgO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\nZr780kI1q2CFGQwSxM1048+jwo2/fdkenVxgWC5jWW1Evikh3ZSQbz2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B8noJ7tM9RZlN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\nTQAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f50aef7c3c8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(cmopen, color='blue', label='open')\n",
"plt.plot(cmhigh, color='green', label='high')\n",
"plt.plot(cmlow, color='magenta', label='low')\n",
"plt.plot(cmclose, color='red', label='close')\n",
"\n",
"\n",
"\n",
"plt.legend(loc='upper left')\n",
"\n",
"plt.xticks(rotation=60)\n",
"\n",
"plt.show()\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**How to Select a Time Window **\n",
"\n",
"We have selected specific time windows from the data set and we can compare open and close prices by placing them parallel in two seperate graphs"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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SpTJspADke1WcknY5XbegcQYpaARIVmpSkbK6dAl++klPVpaGgQPN+Pg4u0U3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"text/plain": [
"<matplotlib.figure.Figure at 0x7f50ae0df5f8>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x7f50aeb2b9b0>]"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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bxv3NRlVpz/WaUG7yHjduHOPGjbvj9VWrVt3xWlhYGGFhYcVe02g0zJkzpwoh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\nw/AmIiKSmP8HC0zVB8+4LUcAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f50aec73518>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Select Time Window based on YYYY-mm-dd\n",
"\n",
"view = cmopen['2017-08-14':'2017-07-14']\n",
"plt.subplot(2,1,1)\n",
"plt.xticks(rotation=45)\n",
"plt.title('Open 2017-07-14 to 2017-08-14')\n",
"plt.plot(view,color ='blue')\n",
"\n",
"\n",
"view = cmclose['2017-07-14':'2017-06-14']\n",
"plt.subplot(2,1,2)\n",
"plt.xticks(rotation=45)\n",
"plt.title('Close 2017-06-14 to 2017-07-14')\n",
"plt.plot(view,color ='violet')\n",
"\n",
"plt.tight_layout()\n",
"plt.show()\n",
"\n",
"# Select Time Window based on YYYY-mm\n",
"\n",
"view = cmhigh['2017-07':'2017-06']\n",
"plt.xticks(rotation=0)\n",
"plt.title('High 2017-06-14 to 2017-07-14')\n",
"plt.plot(view,color ='green')\n",
"\n",
"\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Plotting moving averages**\n",
"\n",
"to plot moving averages first we need to calculate moving averages\n"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py:1: FutureWarning: pd.rolling_mean is deprecated for Series and will be removed in a future version, replace with \n",
"\tSeries.rolling(window=2,center=False).mean()\n",
" \"\"\"Entry point for launching an IPython kernel.\n",
"/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py:2: FutureWarning: pd.rolling_mean is deprecated for Series and will be removed in a future version, replace with \n",
"\tSeries.rolling(window=2,center=False).mean()\n",
" \n"
]
}
],
"source": [
"cm_open_ma=pd.rolling_mean(cmopen,2)\n",
"cm_close_ma=pd.rolling_mean(cmclose,2)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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8/bUJh8M97NKrl7uXplGj/O+lUQref9/MCy/4YLVq9O9vZ9q0rDzrMbmiIP9O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\nEUIIIYTf+v/Nzai96q6e7QAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f50aece02b0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# view = cm_open_ma['2017-08-14':'2017-07-14']\n",
"plt.subplot(2,1,1)\n",
"plt.xticks(rotation=45)\n",
"plt.title('Moving Average Open')\n",
"plt.plot(cm_open_ma,color ='blue')\n",
"\n",
"\n",
"# view = cm_close_ma['2017-07-14':'2017-06-14']\n",
"plt.subplot(2,1,2)\n",
"plt.xticks(rotation=45)\n",
"plt.title('Moving Average Close')\n",
"plt.plot(cm_close_ma,color ='violet')\n",
"\n",
"plt.tight_layout()\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Daily Moving Averages"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/opt/conda/lib/python3.6/site-packages/pandas/core/generic.py:6050: FutureWarning: The freq kw is deprecated and will be removed in a future version. You can resample prior to passing to a window function\n",
" on=on, axis=axis, closed=closed)\n",
"/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py:1: FutureWarning: pd.rolling_mean is deprecated for Series and will be removed in a future version, replace with \n",
"\tSeries.rolling(window=2,min_periods=2,freq=D,center=False).mean()\n",
" \"\"\"Entry point for launching an IPython kernel.\n",
"/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py:2: FutureWarning: pd.rolling_mean is deprecated for Series and will be removed in a future version, replace with \n",
"\tSeries.rolling(window=2,min_periods=2,freq=D,center=False).mean()\n",
" \n"
]
},
{
"data": {
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D4WDw4MHUqVOH0aNH4/F4CA8PZ9q0aej1etasWcOiRYtQq9X07NmTHj164HK5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\nDxYmwJ4DYb/DAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f50aea02940>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"cm_high_ma=pd.rolling_mean(cmhigh,2,2,'D')\n",
"cm_low_ma=pd.rolling_mean(cmlow,2,2,'D')\n",
"\n",
"# view = cm_open_ma['2017-08-14':'2017-07-14']\n",
"plt.subplot(2,1,1)\n",
"plt.xticks(rotation=45)\n",
"plt.title('Daily Moving Average High')\n",
"plt.plot(cm_high_ma,color ='yellow')\n",
"\n",
"\n",
"# view = cm_close_ma['2017-07-14':'2017-06-14']\n",
"plt.subplot(2,1,1)\n",
"plt.xticks(rotation=45)\n",
"plt.title('Daily Moving Average Low')\n",
"plt.plot(cm_low_ma,color ='black')\n",
"\n",
"plt.tight_layout()\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"collapsed": true
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/opt/conda/lib/python3.6/site-packages/pandas/core/generic.py:6050: FutureWarning: The freq kw is deprecated and will be removed in a future version. You can resample prior to passing to a window function\n",
" on=on, axis=axis, closed=closed)\n",
"/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py:1: FutureWarning: pd.rolling_std is deprecated for Series and will be removed in a future version, replace with \n",
"\tSeries.rolling(window=2,min_periods=2,freq=D,center=False).std()\n",
" \"\"\"Entry point for launching an IPython kernel.\n",
"/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py:2: FutureWarning: pd.rolling_std is deprecated for Series and will be removed in a future version, replace with \n",
"\tSeries.rolling(window=2,min_periods=2,freq=D,center=False).std()\n",
" \n"
]
},
{
"data": {
"image/png": 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IR92a7777zpG1JRAIKiMsMgKBF0lOTiYyMpJ58+bVKpNEILiUtWvX8sYbb6CqKtHR0fz9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\ng7//YkJCVIqKkigpKeDRRx8D4KOPFjJ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0NHv9nV69eld7vSdZS+CMk/nttxMEBT0NvEKr\nVsMIC5uKwbCB4uIidu/eSe/efYmM9KwEwRVXdGfWrNkcO3aUhQs/8egaDUnKR6f7Dau1H+6E82+/\nnaCgIN/ngb5Ngd+VkFm2bAl+fn5MnDjJ5fnBg4cSGhrGmjUpdfZb/l7R3D2+FDKK0hZVNVZxLWmi\n5KqrnIG+kpRHWNi1wP+3d97RUZRtH75me+qmUkKHUBTpSo2ggmCjWBAFfJUu0kFQmggIH0oTpEiV\nXkSKgIIiVSB0pPcOCS1tsylb5/tjs5uE3SQbSAhJ5jonR0lmd578svPMPXcdhtUaSFzcavT6WdSp\nY0v6e7SfjNVaGpOpDkrlngwHFz4OGzeuJyYmho8//gS1Wp3F0VaHN0avH51ja5DJZPz440zUajVf\nfTXQMRMls7LrR0kNL6XmySiVSl5+uQnXr1/j+nVb/oA7oaWIiAg8PDycpn5nNQEbUhN+c7NyKTVx\n3D2PDECdOrYn6sOHs07ktveV8fIaD4BavZl792DGjGsUKVKULl26Z/p6V2XYtiog35Qy7MfbuwTh\nHhrNMiyWso6ybjsGw/uIogaNZqmb7y+iUv2F1eqP2ZyxjmZzdczmiqhUWxEEXbbXbAtnl8J+K7NY\nLHz//XfIZDKGDBme9SpFX0TRI0tDJrVy6WiK96giRmMYKtUO/Pxac+pUI0wmE02auE4qzoghQ4bh\n4+PLhAnjXA5izQiF4hSQVSM8WwPG3M6PeRYoNIbM2bNnOHfuLE2bNs/waUepVNK0aTNu377F2bNn\nnvIK8zeuXLy5cBYsljJOoSV7Izy7R0Ymi8TP701Uqr3Au8TEHMBotHnbXnihOmq12tG1NS25EV5a\ntGgBgiDwv/91yvJYtXodSuV/JCe3xWLJ2Zh2aGhFBg8eyoMH91m5chlqtZq6deu7/XpXCb+QmrOx\nebNtY3XXI1O8eIhTQqR73X1tbvTcrFw6duwIcrk8G0+yVl56ybae//5zrqh7FLO5Pkbjq6hUu1Aq\n96NS/cm4cTISEgwMHDgky6Zi9es3RK1Ws2tX2goRNUbjGylN5rLuIOwKT8+fEQQDiYl9gPTTa0RR\ni8HQEoXiqsOTlBly+Snk8giMxuaAPJMjBQyGtghCsiNPyH0SkMmi0uXfrFu3hgsXztOuXXtCQyu6\n8R6CW919K1Sw5T3duLERQbAAvYmL+5OYmJ0kJ7/Ljh22Pemdd1bi4TET0Lv1GwQHBzN+/A8kJibQ\nrt27DBs2mKSkpCxfl1qx5E5HX8kjU2BYv97muny0WulRmje33fC2bdua62sqSKR29S2bq+exWMoi\nk8UgCKlN7Y4ePYxW60eFCqEpc4leR6E4Q1JSN2BNupurSqWiWrUanDlzioSEhHTvndpcLGfCS6dO\nneTo0cO89lozypQpm8XRRry8xiCKShISMo/rPy5ffNHXcXMOCwvDw8PD7ddaLFWxWgNSEn5Tn8hb\ntbI1w/z557NYLFnnyBgMBh4+fOAyidbe1Cszj1jJkrabVm519zUajZw8+R9Vq1Zzu0upQnGKl16y\nfZbsN4+ssHtlvL2/JCLiBHPmiJQuXZaOHT/N8rUeHh7Ur9+Qs2dPc+9e6g34SZrjCYIOjWY+VmsQ\nyckdXR6TnPwJ4F7Sr1ptr1bKOKxk53HDS3K5vYeM7TNhMpn44YfxKJVKBg36yu33sXX3vU9mfXhS\nQ0uHEEUl0B6wTSGPj1/MX3+FotHIefnleLy9hxIY+DxeXqOzNJDANiZn69YdVKpUmfnz5/D6640d\nnaIzIrViKWMjxf4euZ/om/cUCkNGFEXWr1+Ll5c3r7+e+YXVtOnryOXyfFWGff/+ffr378Xw4cPZ\nsGEtFy9ewGzOjdkrGZPaDC/j5mo5waOVS1FRUVy7dpU6dV5EpTqGn19z5PKbJCSMQK+fhKunwRdf\nrIvFYnHaLNKHl1yXAGeHxYttcW93Sq41mkXI5ddJSurs+B1zGoVCwY8/ziQoKJiOHV3frDJGhskU\nhlx+K12OUkBAIG3bfsyNG0ls2CAgin6Zvsvdu5EAFC8e4vQzd3Jk7H1Vbt/OndDSmTOnMBgMTnNy\nMkOp/JegIChdOpATJ467FZY2m+thNDZDoTjNmDFgNIoMGTIUlUrl1jntidb2ShkAo7EpVqsWD49Z\nKJU7M3qpSzSaX5DJ4khK6gm4NnBNpsZYLKVTmtgluDzGjkq1FVGUYzS6HvCaFoslFJOpFkrlzmyF\ndRUKm9fc7pFZuXIZN25c55NPPkvXIywrrNZiCII103OXLl0GuVzOlSuxKaXkqZ107927y7lzl6lf\nvwkJCedISBgOKPD0nExAQA08PGaQVbPCatVqsG3bHrp1+5yLFy/w5ptNmTZtcroRIOl/9xOIoleG\nFXL2RN/Q0Ir4+OROO4xniUJhyBw9epibN6/z1lvvZPkU6ufnT716DTh27Ei+6fI7dOggVqxYyvjx\n4+nevRNhYS9RrlxxmjZ9mT59Pmf27Bns3r0zR1piZ4Rt3kkxwHkq8U8//cibbzbNET1TE36vA3D0\nqC2sVLduIH5+LRGEGOLjp5OYOISMkuDsuQ+PJvyCPbxkeeLwUny8jt9+W03JkqVo1qx5Fkfr8fL6\nHqvVO2XduccLL1TjzJnLfPbZZ9l+beq4gvRVfd279wRg2jQ5WW0pqYm+zpUWtnwFVRZjCnK3KZ47\n/Ygexd7QrXr12jx8+NDxO2ZFQsIwzp+HRYugcuVQtzs+g+s8GfBAp1sEgFb7kVO5fMYY8PCYidXq\nTVJSZka3jOTkj5HJ9Jl6LQXhPgrFUUymhlkato4VGNqmXHfueUOVyn/x9u6LKMowGl8mOTmZKVN+\nwMPDgwED3B/nAWCx2BJ+5fKMvScqlYqyZb25eBGSkzuk+5ndmHzllaaIYiCJiV8RFXWG+PipiKIn\n3t7D8PN7M6XaKWM8PDwYN+4HVq9eT0BAIOPGjaZNm7e4ceP6I0cmIZdfwGx+gYyut8KU6AuFxJBZ\nt842zyOrsJIde5ffx63vf5ps3/43mzb9TqNGsH17A7777v9o3/4TnnvueS5dusDq1SsYNWoYbdu2\n5oUXQqldu6pjUm/OYUYmu+2y9HrmzOmMHfsNR48eZubMaU98ptQS7OtA6o2nSZM1gBmdbhnJyZ9l\n+h6ZTcJOrV5a/0TrXLNmNYmJCXzyyWfI5ZnlCICn5wxksgckJfVNV32RW7gz58kVqQMk0+fJ2Aav\nKvn3X7MjwTAjUkuvnT0ytnyFzMcUaLV+eHl551poyZ2J1+kxo1Tux2wuT40aDQH3w0smUx0GDy6L\n1Qpffz06y89JWp577nmKFCnK7t0705Wim0xN0emWARa02rYolfuzfC+NZjVy+V2SkzshiukTsB/1\n7Npv4hrN8gzfT6XahiCIboWV7BgM7yGKgluzl1SqLWi17yEIyeh0izCb67F48QIiIu7QuXN3ihYt\n5vZ5wb0xBWCiUqVEHjyA+/fTfzZc94/xIDm5C9HRh0lOfg+l8gD+/o3c8s68+mpTdu8Op2XLNhw8\nGM6rrzZi1arlDk+fQnEWQbBkOSgSCkeiLxQCQ8ZsNvP77+sJCAhwu9y0RQvbBfish5eSkpL46qtB\nKBQweza89lo4Awbc5scfZ/L337u5di2S/fuPMn/+YgYOHEyLFm9y+/YtevfukaNN/2Sy2wiCxSnR\nd9GiBYwePYLixUMoVqw4ixbN5+HDJ6sIerSXzPHjNoOjbl1v4uI2YDS6rkhLS0hICYoVK86RI4ec\nwgBWaxlMptpPFF4SRZHFixegUCho3z7z8QKC8AAPj+lYrcEkJubNwDV3sVgqY7UWSTFk0upmZcAA\n2w1vzpzMp/pGRNib4bluNGczZDL2yAiCQKlSpXLVI+Pn5+fIicgKheI/ZLJ4TKbGjqffkyfdS7Zd\nuHAumzdfp169BhlWUmaEfXDnw4cPnNrcG40t0OmWAkZ8fT9war6XHgseHj8iikqSknql+8natb9S\npUo5PvroI4dBY7WWxWh8GZVqb4YDXLOTH2PHag3BZGqU0uE4YyNVrV6Nr297QE5c3GqMxjbo9Xqm\nTZuMt7cPffr0z/C1GZ87614yKtU2Kle2VaZdvZoa1hRFkT17dhEcXITnn6/q9DpRDCI+fhFxcUsQ\nRe8U78wbWXpnAgICmT9/MT/99DMAffv2pEuX/xEdHfVMjSZ4Vijwhsy+ff/y4MF9WrZ8N9Mptmmp\nUKEiFSqEsmvXjjRNp549fvxxIjdv3mDAAAgN7Qg8j6fnTDQaWzt8uVxOaGhFWrV6l6+/HsnSpavp\n3LkbFy9eYOrUiTm2DlfDItesWcVXXw0kKCiI337bSL9+A0lMTGT27J+e6Fz2c8jl19BoRnDkyBWe\ne04ObMVkauTWewiCQJ06L3H//j2XN8TU8FJ2qyhsHDx4gHPnzvL2260oWrRopsd6ek5EJtOTkPAV\nkFvTaXMKAaPxZeTye+k2YkGIo0ULkSpVvPn993WOPBhXREa6HhhpRxQDEYQEMsvBKFGiJHFxscTH\nZ79cNzMePHjA9evXqF37Rbe9Vvbwjcn0suOm8d9/WRsyhw4dZOTIoQQFBTFnzsLH8pLZw0vpq5ds\nGI1votMtQhCS0GrfQ6FwrtIDUKn+QKG4THJyO6xW298kISGB/v170bNnV3S6OFavXs3gwf0dRn/m\nXhkjSuV2zObyWCzuGYN27CML1Op1Ln+u0czDx6c7ouhNbOzvmEzNAJg//2cePnzI55/3IiDAvR4u\naXGnu69Gs5yKKUVQaYdHnj9/jnv37tK48SuZ/g2NxjZERx9K8c4cTPHO/ERm3hlBEGjXrj27du2n\nfv2GbN78O40avcjMmctJTMy6oy8UjkRfKASGjL1a6f3322brdc2bv0liYgL79z+bXX4vXrzAjBnT\nKF1awTffKFI6hm7Gag3C23swSuU2l68bMeJbSpQoyfTpU55oYFlaUodFlgVsDan69u2Jr6+WX3/9\nnYoVK9Ghw6cULVqMBQvmEhX1JIm0XlgsRVGpdnH9+nT0eqhVqyUWywvZehf3wkuuN9SsSJ2rlHkn\nX5nsGh4eC7BYymYZDntWsDfpSzvoTyaLQhCgV6+qmEwmfvllXoavt3tkHu3qa8e9Emxbcuft2znr\nlTl40Oa5yE5+jL0c3WR6mYCAQEqXLsPJk/9lmvB7//59unb9H1arlTlzfnFrDIIr7B7mtOMK0mI0\ntiI+fgGCkIBW+66LsmwRT8+piKJAUlI/AM6dO0uLFq+wYsVSqlevyT//7KFOnTosX76EMWO+AWzX\nh9Xqg0azgkdvxErlPmQyfUpCbPaMM4OhFaKoSBlQ+eg6J+HjMwhRDCI29o+UGVAQFxfLzJnT8ff3\np2fPx/NoZmXICEIUKtVWKlSwPUSlHR65e7fNiHRnLEGqd2ZpindmOH5+LbL0zpQuXYb16//gm2/G\nYjSaGDr0MBUqwKxZe1w+aKft6FsYEn2hABsyGs185PJv2Lx5HSEhIdnqmQHP9hBJURT56quBmEwm\nfvrJjFz+UUqb6nLExa0EFPj6foZc7twLx9vbh8mTp2E2m+nfv1eOVDel7eq7Y8c/dO/+GWq1hpUr\nf3N01tRoNPTp05/ExATmzJn5ROezG0z79tluaHXqvJbt98gs4ddqLZtSRZH98NK2bVvZsGEtlSpV\npmHDzOcYeXmNQxBMKYMh3atWyWuMRltjvLQJv/auvh999CL+/v4sXrwww14YERG3UavVGXY/da+7\nb+5ULh04YOuP4r4hY0KpPIDZXNkRnqhevWamCb9ms5kePTpx924kw4d/m62mhI8SHBxMtWo1OHgw\n3KmVgB2D4T3i4+ciCPFota2Ry086fqZU/otSeRSj8W3M5kosWfILLVq8wsWLF+jW7XP++GMb1avX\nZMuWLYSGVmTmzGlMnz4V8MJgeA+5/LbT5OrUIZHuh5XsiGIgRmNTlMqTyOUX7d/Fy2skXl5jsFhK\nERu7NV2PpVmzphMXF0vv3gMe+6adGlpyXQyhVq9BEEyULt0OIN3MJbs3zB1Dxo7R2Dold+Z9lMpD\naXJnMjZ+5XI5vXv348iR4wwbJkevlzFixHDq1q3BggVz06UKXL9+jbi42EITVoICbcgsY8+eH9Hp\nEvj442i02p6oVBvc7h5Zt259tFq/XOnye+PGdQYM6J2udDI7rFmzin37/uWdd7S0bCmQlDTA8TOz\nuR7x8T8jk8Wj1X6IIDjHfV977XU+/PBjTpw4zs8/P5lRAakemX//fUCnTh2Qy+UsW7aaF1+sm+64\nTz7pRHBwEebPn0NMTPRjny8xsQ9JSV3Ys6cBkL0naDvVq9dELpe79MjA44WXTp06SbdunVCr1Uyf\nPjuLCbgH0Gh+xWSqicHwXrbXn1dYreWxWEqkhFRsSab2OUsaTVE+/bQL0dHR/Pbbapevj4iIcNkM\nz449HGHrcJzo8hh7d9/c8si4W3qtUBxDEBLSTbvOKrw0fvwY9u37l7feaknv3v2ecMW2hoRGo5ED\nB/ZleIzB8CHx8bMQhDj8/Fo5HnA8PacCcPduV7p378SXX/ZDo9GwZMkqxo37wdGJOjg4mF9/3UBI\nSAm++24US5cucvSaSd9TRkSt3oLV6u12mNd5rfbw0hrAgrd3Xzw9p2M2VyQ29i8sltQmd/fv32fO\nnNludUPODFEMRBQVGXpkNJqViKKcwMCuaDQaxxRsg8FAePg+KleukkHyeubnjI//hbi4ZYiiD97e\nw/Dx6Qxk3gwvKOgB48ZZOHv2ffr0GYBOF8fQoV9Sv34tFi9e6OiDBFC9euFI9IUCbMjExv7JkiW2\nG127dl5oNCvRav9HYGA5tNrWeHjMyjBZDWw9N5o2bcadO7dzLAQDtgS6V19txPLlS/j44/cdFVXu\nEhMTzbffDsfTU82MGXEYja3SXdxgayeekDASufwWWm07XN0QxowZT1BQMD/8MC7Lqa5ZIZff4NAh\nGe3b98FsNrNw4VLCwpxbdXt4eNC7d3/0+vgsk0Izw2hshV4/laNH/8Pb24fKlatk+z08PT2pWrUa\np06dcJn4nNpczL3qpcjICDp0aEtSUiIzZ87LYk6PER8f201Mr59I/roMBUymxshkUcjlZ23fccxZ\nCqRTp64oFArmzp3l9ABgn5GUWSglObkjBkMrVKo9aLUf42pjL1HCbsjkXOWSTLaNgwf/JTS0otPo\nhIywD9G0l6UDmSb8bt68kRkzfqRChVCmT5/12NVjacksTyYtBkN79PqfkMmi8fNriVr9KyrVdvbv\nr0GTJv35/fd11K1bn5079/PGG285vb5kyVKsWfM7gYGBDB7cn/XrIzGbK6JWb3Y0p5TLLyGXX08Z\nNvl4HkaD4S1E0QO1eg0+Pp3x8FiMyVST2Ni/0g1HTExM5LPP2pOYmMCAAYPdbl7oGhlWaxGXyb5y\n+VmUyuMYja8jCMUoV648V65cRhRFDh8+SFJSUra8MY9iNLYiOvoAJlMDNJq1+Pm9iUyWcY6ZPdHX\nz68eI0eO5vDhU/Ts2YeoqIcMHtyfBg1qs3ChLbQreWQKAHq9ha1b/yM0tCJlylwmJmY3CQlDMZtf\nQKXaibf31wQG1sDfvy5qtetSQnuX35wYIhkfr6NXr+707NkVURQZPHgoHh6e9OzZ1fHBc4dx48bw\n8OFDhg8PoUwZSEwc6PK4xMQvSU5uj1J5DF/f7tifnu0EBAQyYcIkkpOTGTiw7xNNEz5z5jJvvGHb\nXH7+eQHNmrXI8NhPP+1MUFAw8+b9TGxszGOfMzY2hosXL1CrVp1sla2mpU6dFzEYDJw5c8rpZ6nh\npd1Zhpf0ej0dO7bj7t1IRo4cwzvvtMr0eA+PGSgU50hK6uKI9ecnUvvJ2PJDZDKbIWO1BlC8eAit\nW7/HhQvnnW6u9+7dRRTFLJ5eleh0CzEY3kal2olW2x5InweQ2kvmyQ0ZQYjGx6cHd+++T3y8gXr1\n3L8Bp030tWO/eTxagn358iX69u2Jp6cnv/yyPNOhkNnhpZfq4enp6dacnuTk/xEfPxWZ7CE+Pl2Z\nMgVeeeVMSsHAl2zY8KfL/j52KlasxMqVax371pYt9RGEZNRq2zBed4ZEZo03BsObKBRX0WjWYzQ2\nJC5uk6PrM6SG544cOcR777WlU6esG05mReqYgvTGty0PCJKTbZ18y5cPJSFBz7179zIou84+ohhM\nbOxGkpM7oFQew8/v1QzHTDxasRQcHMzo0eM4fPgk3bv35P79e4SH27xzhSXRFwqwIbNlyx8kJSXx\n7rsfIAhyzOZaJCYOJTZ2N1FRF4iPn47B8BZy+Q18fXumZJCn57XXmiGXy5/YkDl27AivvRbGmjWr\nqF27Djt27GXw4KFs2PAnQUHBfP31ICZNmpBlCOvIkUMsWbKQKlXKMnjwNYzGVzGbM3IfCsTHT8do\nDEOt3ugYRpiWli3b8Oab77B//16WLl30WL/blSuneeONKGJirPz440xatmyT6fGenp588UVf4uN1\nzJv382OdE+DYsaMAvPii+xOKHyWzhF+weWVs4aU/MnwPi8VCz55dOHXqBJ988hm9evXN9JwyeEGH\nFwAAIABJREFU2TW8vCZgtRYhIWHUY689L3l0gKQ9tGQfT9CjxxcAzJ2b3uuWVel1Kip0usUYDG+g\nUm3H17cjkOo1K1q0GHK5/Il7yahUGwkIqItGs9KRbxUWdsZFsqkrDCiVBzGbqyKKqfk+9oTftB1+\n9Xo9nTp1QK+PZ8qUn6hS5bknWnda1Go1DRuGcfHiBbdK0pOTuxAZ+R2tW8OgQeDnF8Cvv25g6NBv\nUCgUWb6+Zs3aLF26CoCPP17LgQOCI7xk6+YrYDS+/kS/k30UgsHwOnFx6xDFVKPPnh/4119baNz4\nVaZPn41M9uS3MVt3X0O60SdgRqNZhdXq55jVZh8eefHiRXbv3oFSqaRBg8xz4dxDTXz8LPT671Jm\nxb2BSuXsDVYoTiKKAmZz+lLvokWL8d1333Po0Al69OjFkCHDcsxYzg8UWEMms9lKVmtxkpM/Q6db\nRUzMXiyWELy9h+Pp+UO64/z8/KlfvyHHjh3l3r3Mp6O6wmKxMG3aZN55pzk3b96gb9+BbNr0B5Ur\nn8XH53Nq1Upg06a/KF26DD/8MJ4RI77K0DNiNpsZPNiWCzNzZghKJSQmDspiBSp0umWYzaF4ev6I\nRrMo3U8FQeD77yfj66tl9OiRbncktXPlyiU++OBd7t2DKVPq8tFHHbJ+EbZqnsDAQObOnY1OF5et\nc9qxGx+P5uFkB3vCb2aGDGQeXho1ahh//bWFJk1eZcKEyVmEC0R8fAYiCMno9RPc7nr6rGG1lsZi\nKYtSuQ+wpAkt2WZa1axZm3r1GrB9+zYuXrzgeF1EhO1Gm1HpdXpU6HRLMRheR63+G1/f/wFGwBb2\nDQkp8di9ZAThPj4+n6LVdkQQ4tDpvuXXXysBULeuJz4+vVAojmb6HkrlYQQh2ZH8nJbq1WsSFRXF\nnTu3EUWRgQN7c+HCebp1+5z33ste9aQ72MNL7uTcRUdH0bLlBjZtgsaNG7Bz5/5sexTCwhozd+4i\nkpKSefttBRcvHkWhOIhSGY7ZXAdRLPJYv4cdk6kpUVEn0el+BdKHjCZO/D+WLl1EtWo1+OWXpW6P\ndMgKV71kVKrtyGT3U2ZB2fKF7IZMeHg4J078x0sv1cPbO6faJggkJfVFp1uFKMrRaj/F03MCqV4i\nKwrFyZRUAtfnLF48hLFj/48vv/w6h9aUPyiwhsz169eoW7c+FSpkPgHVYqlIbOwWLJbSeHl9h6fn\nGNK6F+3hpex2+Y2MjKBt29aMGzeaoKBg1q2bwf/9n4lixaqh1bZHo1mBVtuWihWT2bz5b6pUeY55\n836md+8emEwmp/ebP/9nzpw5RYcOLXnttf2YTC+mc2lnhCgGEBe3Bqs1AG/vgU4zWIoVK87o0ePQ\n6+PT9YrIjISEBMaPH0OTJg24c+ceEyZA9+5ZteFPxdvbm549+xAXF8v8+XPcfl1a7BOva9fOfqKv\nnXLlKuDv78+RI657bFit5TCZaqaEl5yTkxcsmMPcubOpXLkKCxYsybJPkVq9DpVqO0bjaxgM7z/2\nup8FjMbGyGRxKBQnnTwyAN2727wyab1uqR6ZjMMX6VGj0y3HaHwVtXoLvr6fAbZro2TJUty9G+ny\nWskYEbV6NQEBL6HRrMdkqkd09D4GD77H9u3/EBYWRrlyvwAGfH3bZ5qrYPdG2bsdp6VmTZuX9MSJ\n/5g3bzYbNqzjpZfqMWrUd9lYq/vY5y5lFV6KjIygdes3OXr0CB980I6VKzdTpMjjGR1vvfUOU6fO\nIDraRPPmEBXVFUGwPFa1kitslYnpQ8ZLlvzCpEkTKF26LCtW/JajpcWuSrDVantYKfUBzd4oce7c\nuYii+MRhJVcYjW8SG7sNi6UMXl7j8fHpBCQhk11HJtNl2j+msFJgDZmNG/9ixQr3Emmt1nLExm7B\nbC6Pl9ckvLyGYzdmHqfL759/buaVVxqwd+8e3n77BY4dK0KbNr3w9LQ1QEpM7IlePx6ZTIdW+wEh\nIVZ+/30Ldeq8xG+/raZTpw7pylcjIu7w/ffjCQgIYMIE283S5o1xL1nQaq2ATrcCkOHr+z8UigPp\nft6+/Se8/PIrbNv2V6bJx6IosnHjeho1epEff5xEcHARliz5H199hVNX36zo3Lkb/v7+/PzzjGw3\nNrNarRw7dpRy5cpnWMbrDvbGeDdvXs9wDpUtvGR2Ci9t27aV4cO/IigomOXL12TpxhWEWLy9v0IU\nNcTHTyG7PTaeNdKOKxCEaEQx/cDIt956h9Kly/DrryscFWpZNcNzjYa4uFUYjU1Qqzfj69sZMFGi\nREmsVqvbCb8yWQS+vu3w9e2GIBjQ678nNnYrU6duYu7c2VSp8hwbN27EbH6ThIQxyOWRKR1kXVeR\nKJX/IoqCy+oce8LvokXz+fbbEQQHF2HBgiU55j14lNDQipQoUZI9e3ZmOGTw6tXLtGzZggsXztO9\ne09mzJjjdoPQjPj44458++1oIiLgrbducOfOk+bHZMyWLX8wZMgAAgMDWb16bZaNJrPLo2MKBCEG\ntfoPzObKmM21HceVL28b0nj16lXgyfNjMsJiqUpMzA5MpvpoNOvw83sDtdr2MJ1ZR9/CSoE1ZIKC\ngrIVI7RaSxEXtwWzuRKenjPw9h4IWClfPpTQ0Irs2bMzwy6/8fE6jh07wqpVy+nVqxuffdaepCQd\ns2Yp2LTpNMWKncJgaE5c3FKioi6QkPA9SUm90evHIJffQattS0CAgt9+28irrzbl77+30q7du8TF\n2eK1I0Z8TUKCnlGj+lOixEbM5iqOmK27mEwNU0ow4/HzexNPz4nYm1kJgsDkydPw9PRk+PAhLscI\nnD9/jvffb0nXrp/y8OEDBg4czN69h3n/fVuFh32Yo7t4e/vw+ee9iY2NZcGCudl67ZUrl4mLi32i\nsJIde57MsWOuvTKuwkunT5+ie/fOqFQqli5d5dakXS+v0chk90lMHILVWv6J153XpDVkZLKoFCMm\n9QlaLpfTpUsPkpKSHPlXWTXDyxiPlHb0L6NW/46PTzeqVbM1QOza9VMiIyMyea0VjWZxSlL/VozG\nJkRHh5OU1JPly5czbtxoSpYsxerV6/H3t32Wk5L6kpz8EUrlUXx8+uDc3yMRpfIwZnMNp9lEANWr\n2240u3fvRBRF5s1bRLFixbP5O7uPfVxBTEyM00R3sLUFeOedFty8eYOvvhrO2LETciSvBOCLLwYw\naFBNLl2C0FAYMmRJjlaTga0Lco8endBoNCxfviZLL/vj8GhoSa1ehyAYU5J8Ux860t5X/Pz8cnWW\nkS0JeFNKEvBxvL2/AiRDxhUF1pB5HKzW4imemRfw8FiAt3dvwJLS5TeRjRvX8++/u1mwYC5Dh37J\n+++3onr1ylSoUJI33niNvn17smbNaqpVgyNHLHTrVpqEhFFER59Fp/sNo7E19lgrQFJSP5KSuqBQ\nnMbX9xO8vFQsXbqaNm3e48CB/bRp8zYrVy5j8+bfqVevAV263EIQzCQmDuBx/nQGw4fExf2B1VoM\nL6+xaLVtHO7zsmXLMXToSKKjoxkxInUCs04Xx8iRQ3n11Ybs3buH5s3fYM+eg3z99Ui8vLzSdPXN\nnkcGoGvXHvj5+TF79k/o9fFuv84eVnqc/jGPklXCr9VaPiW8tAtBiObu3Ug6dvyQhAQ9M2fOdWsN\nCsVBNJqFmM1VSEzMPBk4v2C1FsNsroRKtR+Z7H66sJKdDh0+wcvLmwUL5mIymYiMvINSqSQoKMjF\nO2aFZ4ox0xCNZh0DBvzHJ598yqlTJ2jR4lVOnTqOTHYNlWoLHh4/4uPTAz+/JgQFlXAYI/Hx04mL\n24jVWo6tW/9k0KC+BAQEsHr1+kcqqWyJ8ibTS2g0v+Lh8WO6lSiVBxEEY4ahXVvCb1kARo4ck2Vj\nxJwgozJs2z7yFlFRD5kwYTKDBn2VI2XfaRk6dCazZwsUKWL7W9etW4N+/b7g8uXMO9a6w8WLF+jY\nsS0mk4kFC5Zk0dbg8bFabSE2u0dGo1mOKMowGNqlO04QBCpUsHllwsKaPHbFpPvYk4DHIoq2v5vZ\nXC2Xz5n/yDpNvZBhs4I3o9W+i4fHMgTBQIsWnzJr1nR69+7hdHypUoE0a+bP88/H8NxzUKWKhtq1\n22CxdCImpj6ZhxAE9PqJyGQRqNVb8PHpS3z8LGbPXoCfnz+LFi2gX78vUCgUTJw4Ek/P97BYSqck\nnz0eJlMjYmL24uPTC7X6T/z9GxIfPwejsTldu37Ohg1rWbfuN9q0+YDY2BjGjh3Fgwf3KVu2HN99\nN8GRM2RHJruBKGocMebs4OPjS48evfj++3EsXDifvn0HZPmaBw8eOMJf7k8ozpjatesgCAJbtmym\nePEQ/P398fPzT/dftboVvr7/YTKtp2PHxURE3GHEiNFZVmjZMOHj0x9BEImPn0Z+6eDrDibTyygU\nthb4rubq+Ppqad++I/Pm/cymTRsczfAe3xvgjU63Bq32PXx81jJ37us8/3wNhg07QcuWTVi5Elql\nqXwXRRUWSyVMptokJn7t6ENy4MB+unf/zPGEX7FiJRfn0qDTLcfP7xW8vL7FYkn1groqu36UESNG\nceXK5cdum59dXn65CYIgsHPndgYMGAzYwp9duvwPs9nM7NnzcyXRGMBqrcaHHx6hVauirFu3menT\np7By5TJWrVpOy5Zt6NdvINWqZd+LEBkZwUcfvUdsbCzTp8+maVP38/CyS1qPjFx+EaXyCEZjU8f8\nqbSULx/K8ePHci2s5IxthITZXBOZ7Ha6KjkJG4KY021rs8GDB+4/haclONjnsV/rLoIQh1b7AUrl\nQRITW9K1qw86nZ5KlSpRpYqGqlVPU63aTnx9bVU3JlN9kpM/wWBogyj6ZPNsCfj5vY1SeYyEhK9J\nTByGKIp8//04pkz5gf79v+S778DLaxLx8ZNITnbdxTJ7uohoNHPw9h6BIBhJTOxDQsIozp+/QtOm\nYVgsFqxWKx4eHgwYMJjPP++NRqNxepfAwDJYrcHExLgOzWRFXFwsdepUQ6lUcOTIaby8vFwed//+\nfWbOnMbixQtITEykatVqbNu2O8uSUXc0ad68SaaD/mQyGf7+VuRyFffvG+nY8VMmT57u1pOth8c0\nvL1HkpT0KXr9kw3MzEly4hpSqTag1dqmexsMb6LTOXfzvXbtKvXr16JatRqcPn2SunXrs3Hj1ic6\nryDo0GrboFTaPnPr1yvp2NFMUpLI//1fc3r0+BSr9bmUcGf6z8fZs2do3fpNEhL0LFu2mtdeSy0V\ndqWJQnEcP783EEU5sbHbsView8+vGQrFUaKibiCKz84smzfeeJWTJ09w4cJ1/vprC336fI5KpWLh\nwqVPZARk97NitVr588/NTJs2mRMnbNdV06av07//YOrVc29UTFxcLK1avcm5c2cYNuwb+vf/8rHW\n7j5GgoODMBpfxmx+CU/PKSn9jJwfGjdt2sDEieNZs2ZTjufq5Hdy+94cHOz63ioZMpmiR6tth0r1\nLwZDC0ym19BolqFQ2BqoWSxFMRjak5zc0am7bnYRhPv4+zdDLr+OTjcLg8HWAjwyMoLixb0IDHwB\nUBEVdRrwcPkej6OLQnECH59OKBSXMZlqo9P9wtSp6xg3bjStWr3Lt99+52gJ77xmHUFBJTEamxEX\n93gDFgF++GE8kyZNYNSo75z6sNy7d48ZM35kyRLb/J6QkBL07TuQDh3+52ihnhnuaBIdHcXJkyeI\njY0hJiYm3X/t/6/THSMmxkBYWBumTVvgVqKkTHaDgIC6iKIX0dFHHOXJzwI5cQ0JQhRBQeUAW2VH\nfPxsl8f9738fs3WrLVn6vfc+4OefFz7ReW0ko1QexmIJwWoty4kTJ+nYsR337t3l00+7MH78D05/\no1u3bvL2269z924ks2bN44MP0ocNMtJErV6Lr28nLJayxMZuJiCgJmZzDWJjH2/ESG4xYcJ3TJny\nA++805rNm39Hq/Vj2bJf3TYeMuJxPyuiKLJr1w6mTZvM/v17AahXrwHPP18VuVyOXK5I+a/tSyaT\noVDYvvfPP39z+PBBOnfuxv/936QcD4e5IjCwHFarFkFIRhASiIq6SE7utYUByZDJBk/3Q5SIVtse\nlcoWexZFBUbjmyQnd0xp/JRz0Tm5/BJ+fs0QhHji4taktPoGD4+peHuPQq8fRVJSxr1jHl8XPT4+\ng9BoVmK1+qDXTyMi4tUsK4Lk8lMEBDQiKakLev3UxzivjdjYGOrUqYZarebIkVN4enpy795dfvpp\nKkuW/EJycjIlSpSkX79BfPxxR7cMGDs59Vnx8JiMt/dodLrZGAzu9MsR8fVti1r9NzrdXAyGj554\nDTlJTuni798AheIMiYl9SUhwXV68f/9e2rSxtb3v1asfo0aNfeLzuiIi4g4dOnzImTOneOWV15g/\nf7EjMfPhw4e0bNmcK1cuM2bMeD7/3Dnkk5kmnp5j8fKaiMVSArn8DomJA0hIGJ0rv8fjcuBAOK1a\n2bpqBwcX4ddfN1C1avamwrsiJz4rBw8eYPr0yWzb5n4bi3feac28eYueQh6KDftnGSApqRN6/bQM\nj5UMGdfklSEj5chkiS3J0NaNNZDk5HaIYnCunMliqUhc3Cr8/Frh6/tJyqTXinh6zsRq9SU5+clb\ncbvGOyVPpgk+PoPw9e2MStUOo7EJohiI1Wr7EsWgFFe67enInuib3YqlR/Hz86dbtx5MmTKRqVMn\nkpiYwJIlv2AwGChZshT9+g3io486ZMuAyWkMhjZ4e4/G03MiMtldzOb6mEy1yeiJTaX6HbX6b4zG\nV5wSBgsSRmNjFIozWK0Ze5saNGjECy9U5/Tpk9ksvc4eISEl2LTpLz7/vDN//72Vt99+neXL1xAQ\nEEiHDh9w5cplevfu79KIyYrExOEoFOdRqzcBuGyEl9fUqfMiRYoURaPxYM2aDZQr9+xUx9WrV5/l\ny9cQEXGHuLi4lNC1BYvFgtlsxmKxOv5tsVhQqVTUq9fgqRkxYO8lYzNk7CMJJPIHOe6RGT9+PCdO\nnEAQBIYNG0b16hk378kfHpmnj0q1Hq32UyyW4hgM7fH0nExi4kASEr7N9HU5oYtcfgkfn84olSdc\n/lwUlSlGTSCQjEJxhbi4JRiN7iS+ZkxMTDS1a79AQoIegNKly9Cv3yDatWv/RP03cvKz4uvbPt00\nbFFUYjbXxGSq7/gSxWAEIQ5//5eQyWKIidn/xGHH3CCndFEowvHze5O4uLUOD6Ir/vhjE926fcrm\nzX/nWuWJHYvFwrffDmfOnFkEBQVRoUJFDh4M56OPOjBtWsbDGrPWRI+/fwtksptERZ0jo+6qeUlU\nVBQeHh5POEQxPQV9v7Xj4/M5Gs0KzOYKxMQcI7NCjcKiSXYpEB6ZQ4cOcePGDVavXs2VK1cYNmwY\nq1c7JwBKZI7R+C56/e2UsQmTEUUNiYlfPJVz2zod/4NKtRtBuI9M9hCZLAqZ7CGCEOX4f5nsNjJZ\nHKKoyWTek/v4+wcwYsQoVqxYRufO3fjww4+fuGFXTqPTrUAQ7qFUHkj5CkehOI5SeRiwJfKazRUQ\nRV/k8rskJAx/Jo2YnMRsbsDDh/dI21bAFW+/3ZIbN+49lb+pXC5n7NgJlCtXgeHDh3DwYDjNm7/B\nlCk/PWGuhTcxMduQyeJ4Fo0Y4IkaRBZ27JVLBkP63jESzz45asiEh4fTrFkzACpUqEBcXBx6vT4H\nZ1EUHpKSeiOT3cTTcw7JyZ888fyS7KHGaHSnysGIbaq2czXT49ClSw+6dHEucX+WEMWiGI2tU3oC\nga052tE0hs1hZLIrmM2VSUzsn6drfXq4F/J72oZp587dqFixErt372TgwCFuDUXMGk+s1pzzdkg8\nOyQnf4BMdp2kpM55vRSJbJKjoaWRI0fSpEkThzHTvn17xo0bR7ly5VwebzZbUCieXgw0/2EB9gCN\nKEj9Rwo2VuA8UAx4dqqUJCQkJAoquZrsm5WNFBOT+FjvW7jiky8ChpSvzClcurhH3mhiL1d/dv8W\n0mfFGUkT10i6OCNp4pq8ypHJ0REFRYoUSTen5/79+wQH506Fj4SEhISEhIREjhoyjRo14q+/bH0C\nzpw5Q5EiRaT8GAkJCQkJCYlcI0dDS7Vr16Zq1ap89NFHCILAqFGjcvLtJSQkJCQkJCTSkeM5Ml9+\nmdszMSQkJCQkJCQkbOTpiAIJCQkJCQkJiSchR3NkJCQkJCQkJCSeJpIhIyEhISEhIZFvkQwZCQkJ\nCQkJiXyLZMhISEhISEhI5FskQ0ZCQkJCQkIi3yIZMhISEhISEhL5FsmQkZCQkJCQkMi3SIaMhISE\nhISERL6lUBgy0dHRxMTE5PUynjni4uIcukh9EW0kJSWRmPh4U9kLMnv37uWPP/7I62U8c9y8eZN7\n9+7l9TKeSaxWa14v4ZlCuoacyanrR/7tt99+++TLeXb5559/mD59Ort27aJ69epotdq8XtIzwe7d\nu5kyZQorV65Eq9VSsWLFvF5SnrNjxw5mzpzJ+vXrUalUhISEoFKp8npZec6hQ4f49ttvOXToEM2a\nNZMGwWIz/CMjI+nVqxc6nY6yZcvi4+OT18vKc44fP87BgwepUqUKgiAgiiKCIOT1svIc6RpKT05f\nPzk+a+lZQqfTsXDhQoYOHcpzzz2HQqHAaDQW+pvT+fPnmT9/Pt999x137txh9uzZvPbaa4Val1u3\nbrFgwQLGjBnDgwcPWLx4MVFRUTRt2pSQkJC8Xl6esX//fmbNmsX06dM5d+4cJpMJsD1ty2SFwqHr\nEkEQCAkJoUyZMsTFxbF27VpatWpF6dKl83ppeYbFYmHKlCkEBQWRnJzsGB5c2I0Z6RpyJqevnwKt\notlsRi6X89xzz5GcnMzQoUPp3bs3a9euRa/X5/Xynjr28FFUVBTFihWjTJkylCpVCplMxpQpU9i4\ncWOh1AUgISEBmUxG+fLlqV+/Pn369OHs2bPs2LEDo9GY18vLE3Q6HeHh4QwYMIDKlStz9+5dZsyY\nAVBoN2A7ZrMZi8VC0aJF0Wq1eHt7s337dg4fPsyVK1fyenl5glwux9PTk9q1a3P16lVWrlwJ4DBm\nCiN6vZ69e/fSv39/6RpKg9VqxWq1UqxYsRy5fgpkaOnOnTt4enri5eXFvXv3WLt2Lf/++y+NGzem\nbt26rF+/HlEUef755/N6qU+VqKgoPD09USqVlCxZkhIlSjBr1iwqVqxIrVq1WLt2LVarlapVq+b1\nUp86QUFBXLx4kZs3bxIaGkpISAjFixdn2bJleHt7ExoamtdLfOqoVCqqVatG2bJlAahduzYnT56k\nSJEiBAQEFMon7Tt37uDh4YHJZEKtVju+mjdvzh9//MGCBQuoW7duofLMREZG4unpiUwmo0yZMjRp\n0gSLxcLp06e5desW1atXRxAETCYTcrk8r5f71IiOjkar1VK9enXKlSsHQK1atQr9NQS2h2qZTIZG\no8mR66fAGTLh4eGMHTuWkydPcuHCBRo0aEBUVBQXLlygd+/ehIaGUrp0aZYsWULTpk1Rq9V5veSn\nwr59+5g6dSpHjhwhKSmJatWq4ePjQ61atWjYsCFly5alZMmSLFmyhNdff71QhJnCw8M5ffo0FStW\nRBRFDAYDly5dQqfTOQw9f39/Nm3aRNOmTQvNJhweHs6pU6eoVKkSarXakbRpsVg4fPgwDx48oGbN\nmoUubGDfW06fPs2lS5eoWLEiDx8+5PDhw/j7+7Nu3Tpq1qxJcnIyxYsXx9fXN6+XnOuEh4czbtw4\njh8/jtFopEGDBiiVSooWLYrZbObs2bPo9XquXLnCzZs3KV++fKH4vOzbt49JkyZx5MgR4uPj0Wq1\n+Pr6YjKZOHLkSKG8htLut/bf98aNGxw5cuSJr58C5du6c+cOEydOZOjQobRp04bo6Gg0Gg1Nmzal\nePHizJo1C6PRiE6nw9fXF4WiQKcIObh16xYTJkygV69evPzyy8TGxjJt2jSuXbuGt7c3t27dAmwV\nO97e3gX+hi2KIklJSSxevJhBgwaxYcMGBEHglVdeoWzZsly8eJFVq1ZhsVgwmUyOp82CTlpdvvzy\nSzZu3AjYXOCiKKJUKmnXrh2//fYbCxcuBCgUGzCk31tat25NdHQ0Dx8+pH79+iQkJDBmzBi+/PJL\nvvjiCzw8PPD09MzrJec6V65cYeLEiQwZMoSaNWuyd+9e5HI5oiji5eVFWFgYzZo1Y9WqVUydOpUK\nFSoUis+Lfb/t06cPjRs3JiYmhpkzZ3L16lXUajVt27YtVNfQo/utfV8BqFu3LomJiU98/RQoj0xi\nYiIXLlygY8eOhISEsH37dhISEmjRogXly5fn5s2brFixgkOHDtG/f3+KFy+e10t+KiQlJREREUG7\ndu0oX748RYoUITY2lm3btuHv78+ePXuYNWsWhw8f5ssvv6RYsWJ5veRcRRAElEol0dHRvPXWW0ya\nNAkfHx+qVatGpUqVsFqtnD17loULF3L69Gl69+5NcHBwXi8713lUl4kTJ6LVah0hWLPZjJ+fHzVr\n1mTRokU0b94clUpV4DdicN5bdu3aRXR0NLVr1yYyMpL333+fevXqOfQqDBVMN27cQKfT8eGHHxIQ\nEMCqVauIjIzk8uXL+Pv7ExQUxIEDBzh8+DA//fQT5cuXz+slPxVc7bcxMTH8888/VK5cmVKlSlGz\nZk0WL15cKK6hzPYVURS5e/fuE18/Bcol8WguQ8WKFdHpdABUqFCBL774ApPJhNFoxMvLK6+W+dTx\n9fXlzJkzzJgxg969e1OqVCmaNWuGwWAgMjKS1q1bU7duXUJCQihSpEheL/epYDQaCQkJoVmzZoSG\nhtKjRw9EUeTDDz+kSZMmNG7cmKioKJRKZaEq2c9Ilw8++AClUoler+f5559n4cKFaDSavF7uU+PR\nvaVChQqOvaVDhw7pji0s4erQ0FDKlCkDwPr162nevDnBwcHcuHGDdevW0a1bN8xmM5O8JEcIAAAN\nDElEQVQmTSo0RgxkvN8mJSVx6tQpSpYs6biGCstnxdW+YrVaadu2bY5cPwXGI2OxWNBoNNSpU8fx\nvWvXrmGxWKhZsyZbtmxhz5491KpVq9B8eMCmi1qtpnHjxsydO5f4+Hhq1aqFn58fN27c4NSpU7z1\n1lsUK1as0Bh3oiiiUCgcm2uRIkV48cUX+eabbyhdujTx8fHs2rWLunXrFqqbdUa6jBw5kjJlyqDX\n6/n33395/vnnUSqVBfopMi1Z7S1bt25l9+7dVK9evVCEICFVk5o1awK2h8YGDRpQqVIlZDIZx48f\np0WLFrzwwgsEBATk8Wpzl7Q5Lpntt7dv3+b48eO88sorAAU6tSGtJlarNcN9pXTp0uj1enbs2MFz\nzz332NdPvr7q0naOtOd1iKLoKPXT6/UYDAZ27NjBihUraNasWYHP/wC4ePGio4RNLpdjsVgoVqwY\no0aN4q+//mLq1KkA+Pj4EB8fXyg62abV5NEbsNVqpUaNGqxatYo+ffowYsQIGjVqVChu1O7q0rt3\nb4YNG0ZYWBhyubzAa/PoNQQZ7y3Lly+nWbNmBfrGBK41se/BPj4+jp/FxsYSERFBXFxc3iz0KZP2\nWpDL5ZjNZpf7rZeXFwkJCSQlJeXVUp8aaTWx59jZeXS/HT58OGFhYU90/eRbj8yBAweYN28eGo2G\nwMBAlEqlwwq8ffs2Wq0WpVLJL7/8wuXLlxk5cqSjBK4gEx4ezvDhwwkNDSU0NNTRdEkQBORyOa1a\ntWLBggWcOnWKP//8k6FDh1K0aNG8Xnau4koTIN1nBeDy5ctcuXKFSZMmFdrPCki6uKNLYdtbMtJE\nJpNx+/ZtvLy8+Prrr9mxYwfbtm1j7NixhSIH8ciRIyxcuBC9Xo+Xlxc+Pj4IgpDpflvQw/euNIHc\n3VfypUfmxIkT/PDDD1SpUgWNRuPIcBYEgVOnTtG1a1euX79OqVKl8PLyYsiQIYUiRnvgwAEWLFhA\nixYt2L17N3q93mHEnDx5knbt2mGxWJg3bx6DBg1iwYIFVKhQIa+Xnatkpon9s3Lp0iVMJhPHjx/n\n+++/L/CagKRLRmSlS7du3Qrd3uLOZyUmJobJkyfTv39/5s+fXyg+K/v372fSpEmUKFGC7du3c/Hi\nRSD1PvThhx8Wuv02K026dOmSO/uKmA/Zv3+/OHr0aFEURfH+/fvismXLxH/++Uc8cuSIuHbtWnHf\nvn2OYy0WS14t86ly8eJF8Z133hH/++8/URRF8aeffhJv374tiqIo6vV68ZdffkmnS2Egu5pYrdY8\nWefTRtLFNdnVpTDsLdK+4hqLxSJOnz7d8buvXr1aHD16tHjq1Cnx4sWL4po1awqdLtnVJCf3FUEU\n81/v6PPnzzNz5ky++eYbfvjhB0fjHIvFQvPmzWnYsCGQ2pK/oMfz7Tx48IDg4GCsViuTJk1CoVAw\ncOBAwBbTL4yDytzVRCwkTansSLq4Jju6QOHYW6R9xTUzZsxg586djBgxgkGDBhEWFobJZKJIkSK8\n+uqrjkTowoS7muT0vpJvcmTCw8P566+/OH/+PGFhYZw7d44JEybQunVrevbsSfny5blz5w5qtZpK\nlSoBOGKVBZnw8HC2bNnC+fPnqVq1Kmq1GkEQqFmzJps2bUKj0VCmTJlC0anXzuNoUtA/JyDpkhGP\nq0tB1kbaV1xj1+Xq1at06tQJo9HIpUuXKFGihKPq8eTJkwQHBztGexR0HkeTnL528kWOzLFjx5g+\nfToBAQFcvXqVjh070rt3b8LCwhzdEUuVKoUgCJw+fTqPV/v0sOsSFBTErVu3aN++PVFRUYCtFr9e\nvXpcvXrV8b3CgKSJayRdXCPp4oykiWvS6nL+/Hnatm3L22+/Tb169bhw4QIAlSpVwsPDo9Dch54V\nTfKFR2br1q0EBATQuXNnGjduzLVr15g7dy6TJ0/m7t27/P7775w/f559+/bRr18//Pz88nrJT4W0\nuoSFhXHv3j1++uknXn/9dby9vVEoFPz66694enpSqVKlAv0EaUfSxDWSLq6RdHFG0sQ1aXVp0qQJ\nt27dYs6cOXTp0oUrV64wd+5cLBYL27Zto3fv3oWikeazokm+MGQsFguXL18mNDQUb29vGjVqxOXL\nl5k9ezaTJ0+mVKlSFC1alDZt2jg6TRYGHtWlQYMGRERE8OOPP9KyZUtCQkIoVaoUlSpVKhQt00HS\nJCMkXVwj6eKMpIlrHtWlYcOGXLt2jZkzZzJx4kQSEhKwWCx89tlnBb4c386zoskzacg8mggkl8vZ\ntm0bycnJlC9fHpVKRVhYGKdOncJkMtGgQQNKlChR4C1gd3Rp0KABly9fxmQyUalSJYoVK1agNxtJ\nE9dIurhG0sUZSRPXuKNLo0aNOHv2LDKZjPfee48aNWoU6E7Gz6omz6Qho9frUavVjsoAb29vSpcu\nzbJlyzCZTGi1WrRaLadPn0ahUFC1atU8XvHTwV1dTp48iVqtLhS6SJq4RtLFNZIuzkiauCY79yFB\nEHjhhRfyeMW5z7OqyTNnyISHh/PFF1/QoEEDAgMDAZv7qkiRIpQsWZKdO3dy5swZtm/fzunTp+nQ\noQP+/v55vOrcR9LFGUkT10i6uEbSxRlJE9dkV5eOHTsWeF2eZU2eqT4y4eHhzJ8/n3LlytGqVSuq\nV6+OxWJBLpdz9OhRTp8+zcsvv4zRaOTs2bO89NJLlCpVKq+XnetIujgjaeIaSRfXSLo4I2niGkkX\nZ555TXKstd4TcuzYMbF9+/biiRMnxF27dokDBgxw/Ozhw4fiu+++K+7cuTPvFphHSLo4I2niGkkX\n10i6OCNp4hpJF2fygyZ5bsjY2xRv2LBBPH36tOP733//vXj16lXHvyMiIp762vISSRdnJE1cI+ni\nGkkXZyRNXCPp4kx+0iTPG+IlJCQA0KpVK6pWrYrFYsFoNCKXy9m/f7/juII+oflRJF2ckTRxjaSL\nayRdnJE0cY2kizP5SZM8TfY9cuQI48ePp1ixYpQoUcLxfYVCQcmSJZk8eTKBgYFUqFCh0DRdAkkX\nV0iauEbSxTWSLs5ImrhG0sWZ/KZJnhoyu3btIioqihMnThAQEECJEiUQBAGz2Yy/vz8lS5bkt99+\nIyQkhOLFi+fVMp86ki7OSJq4RtLFNZIuzkiauEbSxZn8pkmeGjJ79+6lXLlyhIaGsnHjRgIDAylR\nogQymS3iZZ+qWr16dby8vPJqmU8dSRdnJE1cI+niGkkXZyRNXCPp4kx+0+Spl1+fPXsWq9VK8eLF\nCQgIQBAEYmNj2bZtG3v27OGTTz6hbt263L9/nyJFijhKvAo6ki7OSJq4RtLFNZIuzkiauEbSxZn8\nrMlTNWT27t3L7NmzKV26NEqlkpCQED7//HMAHjx4wO7duzl8+DBBQUEkJiYyePBgPD09n9by8gxJ\nF2ckTVwj6eIaSRdnJE1cI+niTL7X5GmVRxkMBrFXr17ijh07RFEUxXPnzom9e/cWJ0yYkO64YcOG\nic2aNRMvXbr0tJaWp0i6OCNp4hpJF9dIujgjaeIaSRdnCoImTyVH5t69e8THx6PT6ahYsSLFihUj\nMDCQGjVqsGXLFu7cuUPt2rUJDw9n7dq1zJw5kwoVKuT2svIcSRdnJE1cI+niGkkXZyRNXCPp4kxB\n0STXDZldu3YxduxYjh49yooVK7h+/TqNGzfGy8sLLy8vihcvztGjR6lduzaBgYE0a9aMsmXL5uaS\nngkkXZyRNHGNpItrJF2ckTRxjaSLMwVKk9x090RGRoqdO3cWr127JoqiKPbo0UOsX7++2KJFCzEy\nMlIURVG0WCxinz59nkl3VW4h6eKMpIlrJF1cI+nijKSJayRdnClomihy00hSKpUYDAZHZvO7775L\nq1atiImJoWvXrgwYMIAHDx6g0+nw8fHJzaU8U0i6OCNp4hpJF9dIujgjaeIaSRdnCpomuRpaUiqV\nlCxZkqpVqwJw4cIFdu3axaBBgwgKCuLOnTucO3eO/v37F/jpoWmRdHFG0sQ1ki6ukXRxRtLENZIu\nzhQ0TXLdI9OgQQPHvz09PbFarQCYzWa8vLwYN25cbi7hmUTSxRlJE9dIurhG0sUZSRPXSLo4U9A0\neapDIwMDA6lcuTLHjx9n9erV1KxZ82me/plF0sUZSRPXSLq4RtLFGUkT10i6OJPvNXmaCTm3b98W\na9SoIb777rvilStXnuapn2kkXZyRNHGNpItrJF2ckTRxjaSLM/ldk6c6a8nb2xuz2Uy/fv0oV67c\n0zrtM4+kizOSJq6RdHGNpIszkiaukXRxJr9r8tRnLZnNZhSKXE3NyZdIujgjaeIaSRfXSLo4I2ni\nGkkXZ/KzJk/dkJGQkJCQkJCQyCmearKvhISEhISEhEROIhkyEhISEhISEvkWyZCRkJCQkJCQyLdI\nhoyEhISEhIREvkUyZCQkJCQkJCTyLZIhIyEhISEhIZFv+X8O881asFOTIAAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f50aeaae240>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"cm_high_ma=pd.rolling_std(cmhigh,2,2,'D')\n",
"cm_low_ma=pd.rolling_std(cmlow,2,2,'D')\n",
"\n",
"# view = cm_open_ma['2017-08-14':'2017-07-14']\n",
"plt.subplot(2,1,1)\n",
"plt.xticks(rotation=45)\n",
"plt.title('Daily Moving Standard Deviation High')\n",
"plt.plot(cm_high_ma,color ='yellow')\n",
"\n",
"\n",
"# view = cm_close_ma['2017-07-14':'2017-06-14']\n",
"plt.subplot(2,1,1)\n",
"plt.xticks(rotation=45)\n",
"plt.title('Daily Standard Deviation Average Low')\n",
"plt.plot(cm_low_ma,color ='black')\n",
"\n",
"plt.tight_layout()\n",
"plt.show()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.1"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
| 0001/480/1480273.ipynb | s3://data-agents/kaggle-outputs/sharded/034_00001.jsonl.gz |
{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "5d0fdfb1-c1e6-470b-8334-b8f9788f2144",
"_uuid": "c1191da529264ab804bd48aded36064e87328c1b",
"collapsed": true
},
"source": [
"Poonam Ligade\n",
"\n",
"5th Sep 2017\n",
"\n",
"---------------------------------------\n",
"\n",
"\n",
"1. [Overview](#overview)\n",
"\n",
" 1.1 [Import Libraries](#import)\n",
" \n",
" 1.2 [Load data sets](#load)\n",
" \n",
" 1.3 [Visualize trips in new York city map](#newYorkMap)\n",
" \n",
" 1.4 [Explore data](#explore)\n",
" \n",
" \n",
"2. [Analyzing Categorical and numerical variables](#variables)\n",
"\n",
" 2.1 [Univariate Analysis](#variables)\n",
"\n",
" 2.2 Bivariate analysis\n",
"\n",
"\n",
"3. [Feature Engineering](#datetime)\n",
"\n",
" 3.1 [Date time Features](#datetime)\n",
" \n",
" 3.2 [distance and Speed](#distspeed)\n",
" \n",
" \n",
"4. [Model and Prediction](#model)\n",
" \n",
" 4.1 [Random Forest](#model)\n",
"\n",
"<a id='overview'></a>\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "f04b1d02-1f58-4dfa-a9d3-fb7b6736d0dd",
"_uuid": "bb12664c0b894f6bc520e0236482cefd27819b84"
},
"source": [
"<a id='overview'></a>\n",
"\n",
"## Overview\n",
"\n",
"Here, the challenge is to predict journey time of taxi trips in New York city, based on features like pickup timestamp and ride start and destination co-ordinates(longitude and latitude).\n",
"\n",
"Hang tight. Lets start the fun ride.\n",
"<a id='import'></a>\n",
"### Import Libraries"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"_cell_guid": "8e8d1379-8778-4ff7-9362-78ed69314942",
"_uuid": "dc52543b924baa39e69753c2edcba64f115d6643",
"collapsed": true
},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt\n",
"%matplotlib inline\n",
"#plt.style.use('ggplot') \n",
"#plt.rc('font', size=12)\n",
"from mpl_toolkits.basemap import Basemap\n",
"from matplotlib import cm\n",
"import seaborn as sns\n",
"sns.set(style=\"white\", palette=\"muted\", color_codes=True)\n",
"import pandas as pd\n",
"import numpy as np\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "d52ed292-509e-40a1-9d00-182ff2fb25e9",
"_uuid": "ea928ae1498b486af95f82360bcbf6d3de63ce49"
},
"source": [
"<a id='load'></a>\n",
"### Load Data sets"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"_cell_guid": "9f9e63ea-bc6e-474a-9a26-75a424807126",
"_uuid": "88cead602cbc05d44b1dc7e7273144db658b80d3"
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>id</th>\n",
" <th>vendor_id</th>\n",
" <th>pickup_datetime</th>\n",
" <th>dropoff_datetime</th>\n",
" <th>passenger_count</th>\n",
" <th>pickup_longitude</th>\n",
" <th>pickup_latitude</th>\n",
" <th>dropoff_longitude</th>\n",
" <th>dropoff_latitude</th>\n",
" <th>store_and_fwd_flag</th>\n",
" <th>trip_duration</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>id2875421</td>\n",
" <td>2</td>\n",
" <td>2016-03-14 17:24:55</td>\n",
" <td>2016-03-14 17:32:30</td>\n",
" <td>1</td>\n",
" <td>-73.982155</td>\n",
" <td>40.767937</td>\n",
" <td>-73.964630</td>\n",
" <td>40.765602</td>\n",
" <td>N</td>\n",
" <td>455</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>id2377394</td>\n",
" <td>1</td>\n",
" <td>2016-06-12 00:43:35</td>\n",
" <td>2016-06-12 00:54:38</td>\n",
" <td>1</td>\n",
" <td>-73.980415</td>\n",
" <td>40.738564</td>\n",
" <td>-73.999481</td>\n",
" <td>40.731152</td>\n",
" <td>N</td>\n",
" <td>663</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>id3858529</td>\n",
" <td>2</td>\n",
" <td>2016-01-19 11:35:24</td>\n",
" <td>2016-01-19 12:10:48</td>\n",
" <td>1</td>\n",
" <td>-73.979027</td>\n",
" <td>40.763939</td>\n",
" <td>-74.005333</td>\n",
" <td>40.710087</td>\n",
" <td>N</td>\n",
" <td>2124</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" id vendor_id pickup_datetime dropoff_datetime \\\n",
"0 id2875421 2 2016-03-14 17:24:55 2016-03-14 17:32:30 \n",
"1 id2377394 1 2016-06-12 00:43:35 2016-06-12 00:54:38 \n",
"2 id3858529 2 2016-01-19 11:35:24 2016-01-19 12:10:48 \n",
"\n",
" passenger_count pickup_longitude pickup_latitude dropoff_longitude \\\n",
"0 1 -73.982155 40.767937 -73.964630 \n",
"1 1 -73.980415 40.738564 -73.999481 \n",
"2 1 -73.979027 40.763939 -74.005333 \n",
"\n",
" dropoff_latitude store_and_fwd_flag trip_duration \n",
"0 40.765602 N 455 \n",
"1 40.731152 N 663 \n",
"2 40.710087 N 2124 "
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"train=pd.read_csv(\"../input/train.csv\")\n",
"train.head(3)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"_cell_guid": "ec06a059-1e71-463f-b661-0c2348a774f2",
"_uuid": "b2e3d9611474788b22d0f56c290a0777982c913e"
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>id</th>\n",
" <th>vendor_id</th>\n",
" <th>pickup_datetime</th>\n",
" <th>passenger_count</th>\n",
" <th>pickup_longitude</th>\n",
" <th>pickup_latitude</th>\n",
" <th>dropoff_longitude</th>\n",
" <th>dropoff_latitude</th>\n",
" <th>store_and_fwd_flag</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>id3004672</td>\n",
" <td>1</td>\n",
" <td>2016-06-30 23:59:58</td>\n",
" <td>1</td>\n",
" <td>-73.988129</td>\n",
" <td>40.732029</td>\n",
" <td>-73.990173</td>\n",
" <td>40.756680</td>\n",
" <td>N</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>id3505355</td>\n",
" <td>1</td>\n",
" <td>2016-06-30 23:59:53</td>\n",
" <td>1</td>\n",
" <td>-73.964203</td>\n",
" <td>40.679993</td>\n",
" <td>-73.959808</td>\n",
" <td>40.655403</td>\n",
" <td>N</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>id1217141</td>\n",
" <td>1</td>\n",
" <td>2016-06-30 23:59:47</td>\n",
" <td>1</td>\n",
" <td>-73.997437</td>\n",
" <td>40.737583</td>\n",
" <td>-73.986160</td>\n",
" <td>40.729523</td>\n",
" <td>N</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" id vendor_id pickup_datetime passenger_count \\\n",
"0 id3004672 1 2016-06-30 23:59:58 1 \n",
"1 id3505355 1 2016-06-30 23:59:53 1 \n",
"2 id1217141 1 2016-06-30 23:59:47 1 \n",
"\n",
" pickup_longitude pickup_latitude dropoff_longitude dropoff_latitude \\\n",
"0 -73.988129 40.732029 -73.990173 40.756680 \n",
"1 -73.964203 40.679993 -73.959808 40.655403 \n",
"2 -73.997437 40.737583 -73.986160 40.729523 \n",
"\n",
" store_and_fwd_flag \n",
"0 N \n",
"1 N \n",
"2 N "
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"test=pd.read_csv(\"../input/test.csv\")\n",
"test.head(3)"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "895dd43b-7cb6-4683-ae94-8eb56992c605",
"_uuid": "a36d9973657b8d0118d7e5204cab9f84d2171b68"
},
"source": [
"<a id='newYorkMap'></a>\n",
"## Visualize trips in New York city\n",
"\n",
"First things first! Let's plot beautiful New York city with the help of our pickup and dropoff coordinates."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"_cell_guid": "990ba03a-6de0-4d88-bede-30bee01ee05c",
"_uuid": "5067366e460036c44ecc7f96506f8479cb0c9cc7"
},
"outputs": [
{
"data": {
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ZbchhqNZWrq/hrCRvDgeoaP/4+tYa8LwZomS97pjNchsJwn5npZVV2EpsD1OJ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3r0G3ljiuJopgEH+C24rg/E1Fl7o3kmxjzOwy6EZQw1QXUhMwgiZcyiC6d7C8VhtFpYjbzFju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\n/CcO3IvZZrIMljBDB7q+N8JBZwWPcjM3yowxi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"text/plain": [
"<matplotlib.figure.Figure at 0x7f45c90e2f98>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"#lets remove far away locations\n",
"west, south, east, north = -74.03, 40.63, -73.77, 40.85\n",
"\n",
"train = train[(train.pickup_latitude> south) & (train.pickup_latitude < north)]\n",
"train = train[(train.dropoff_latitude> south) & (train.dropoff_latitude < north)]\n",
"train = train[(train.pickup_longitude> west) & (train.pickup_longitude < east)]\n",
"train = train[(train.dropoff_longitude> west) & (train.dropoff_longitude < east)]\n",
"\n",
"fig = plt.figure(figsize=(15,11))\n",
"ax = fig.add_subplot(111)\n",
"m = Basemap(projection='merc', llcrnrlat=south, urcrnrlat=north,\n",
" llcrnrlon=west, urcrnrlon=east, lat_ts=south, resolution='i')\n",
"x, y = m(train['pickup_longitude'].values, train['pickup_latitude'].values)\n",
"m.hexbin(x, y, gridsize=1000,\n",
" bins='log', cmap=cm.YlOrRd_r);"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "5dd3cdd9-23cb-4d52-ac66-4d77edef8521",
"_uuid": "9e9e4f2c58abe881d3eb8b5256378f7f8ce7f15f"
},
"source": [
"Wow looks magnificent! \n",
"Most of journeys have been to or from Manhatten. Other location where I can see traffic is at 2 airports(John F. Kennedy and LaGuardia Airport)\n",
"Thanks to [this](https://www.kaggle.com/dotman/data-exploration-and-visualization) kernel by dotman for the above map code.\n",
"\n",
"<a id='explore'></a>\n",
"\n",
"### Explore Data\n",
"Let's visualize how many observations and columns are there in the `train` and `test` data sets."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"_cell_guid": "7efb274a-2294-419e-a0f9-ebd82f3fc27e",
"_uuid": "41ee6f7e3ddd505496752ade3ae3dd15986c6eab"
},
"outputs": [
{
"data": {
"image/png": 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zk8ViUUJCgipWrGjdt6gxcHdmzJihMWPGWF/TtwfDuXPnlJmZqUGDBqlPnz7a\nvXs3vXtAdOjQQbGxsQoICFBwcLBGjx5N7+5jDg4ON3zhqa37df12Nzc3Xbp0qcTOtzQprHfOzs6y\nt7dXbm6uVqxYoU6dOtG7+1BhvTtz5oyOHz+udu3aWbfRuzvnUJKDG74H+p7Ztm2b1qxZo8WLF6tt\n27bW7TfryZ1sv9MxULQvv/xSTz75pP7yl78U+j59u7+lpKRo7ty5io2N1YsvvljgmtK7+9c//vEP\nPfzww1q0aJGOHz+usWPHFnif3j1YbN0vevjH5ebmatSoUXr66afVokULbdiwocD79O7+9N577yk0\nNPSW+9C7ohXrSpi7u7sSEhKsry9duqSqVasW5xS4Dd99950iIiK0YMECubi4yNnZWZmZmZKkixcv\nyt3dvdBe5W/P/+1sdna2jDGqWrVqgQ9B3myM/O24czt27ND27dvVo0cPrV69WvPnz6dvDwg3Nzc1\natRIDg4OqlGjhsqXL6/y5cvTuwfA/v375evrK0mqU6eOLl26pHLlytG7B4it/zt5/Rj08I975513\nVLNmTQ0ZMkRS4f8fSe/uLxcvXtTPP/+st99+Wz169NClS5cUHBxM7+5CsYawli1basuWLZKko0eP\nyt3dXRUqVCjOKVCE1NRUvf/++/r0009VuXJlSb/dg5vfl61bt6pVq1by8fHR4cOHdeXKFaWlpWn/\n/v1q0qSJWrZsqc2bN0uSvv32WzVv3lyOjo567LHHtHfv3gJjPP3009qxY4eysrJ08eJFXbp0SY8/\n/vi9OfEH3EcffaSoqCitWrVK3bt312uvvUbfHhC+vr6KiYlRXl6ekpOTlZ6eTu8eEDVr1tTBgwcl\nSefPn1f58uUL/DtG7+5/tv67dv0Y+fvi7qxfv16Ojo4aNmyYdRu9u/95eHho27ZtWrVqlVatWiV3\nd3ctW7aM3t0Fiynmdb1Zs2Zp7969slgsmjhxourUqVOcw6MIK1euVHh4uB599FHrtunTpys0NFTX\nrl3Tww8/rPfee0+Ojo7avHmzFi1aJIvFouDgYHXu3Fm5ubkKDQ3VL7/8IicnJ02fPl0PPfSQTp8+\nrQkTJigvL08+Pj565513JElLly7Vhg0bZLFYNHz4cLVo0eJenXqpER4ermrVqsnX11ejR4+mbw+A\nyMhIrVmzRpI0ePBgNWzYkN49ANLS0jR27FglJiYqJydHb7zxhry8vOjdferIkSOaMWOGzp8/LwcH\nB3l4eGhbhkLbAAAHEElEQVTWrFkaM2aMzfqVlpamkSNHKiUlRRUrVtTMmTPl4uJyj6/M/a+w3iUm\nJqpMmTLWX9Z7eXkpLCyM3t1nCutdeHi49Rf9bdq0UXR0tCTRuztU7CEMAAAAAHBzxf5lzQAAAACA\nmyOEAQAAAIANEcIAAAAAwIYIYQAAAABgQ4QwAAAAALAhQhgAwOrcuXOqXbu21q9fX2B7mzZtimX8\n2rVrKycnp1jGupktW7bIz89Pq1evLtF57saYMWPuy7oAALZFCAMAFPDII49o3rx5unr16r0u5a7s\n3LlTAwYMUPfu3e91KQAAFMrhXhcAALi/uLu7y9fXV/Pnz9eoUaMKvLd27Vp9//33mjVrliQpJCRE\ngwcPlr29vSIiIuTp6anDhw/Lx8dHtWvX1jfffKOUlBQtWLBAnp6ekqSIiAjFxMQoLS1NM2bMkLe3\nt44fP64ZM2YoJydH2dnZmjBhgurVq6eQkBDVqVNHx44d09///nfZ29tba9mxY4fmzZunsmXLqly5\ncpo8ebIOHDignTt3at++fbK3t1fPnj2t+8fGxmrSpEnKyMhQenq6RowYoWbNmqlHjx4aO3asmjRp\novDwcKWnp2v06NH6+OOPtXv3bkmSp6enZs6cKUdHRzVq1EiDBw9WdHS0srOzNWjQIK1atUpnzpxR\nWFiYfH19FRISonr16unUqVOKj4/Xq6++qo4dOxa4lhs3btSyZctkjJGrq6umTJkiFxcXhYaG6syZ\nM7JYLKpbt64mTpxYIn0GANw7rIQBAG7wt7/9TTt37tTPP/9828ccOnRIo0ePVlRUlDZs2KCKFStq\n6dKlql+/vjZv3mzdz8vLS8uWLVOfPn00d+5cSdLIkSM1adIkLV26VGFhYQoNDbXu7+zsrGXLlhUI\nYBkZGQoNDVV4eLiWLl2qv/71r/roo48UFBSkVq1a6eWXXy4QwCQpLCxMf/vb3/S///u/+uSTT6xz\nTJ8+XdOmTdPJkycVHR2t4cOHKycnR+XKldOKFSsUGRmp1NRU7dq1S5KUnp6uBg0aKDIyUs7OzoqO\njtaCBQv02muvacWKFdb5cnJytHjxYs2dO1fTpk1TXl6e9b0LFy4oIiJCS5Ys0RdffKFmzZrp008/\n1cmTJ3Xw4EGtXLlSkZGRqlu3rlJTU2+7BwCABwMrYQCAGzg5OWnUqFGaOnWqFi1adFvHeHl5qXLl\nypKkypUrq1GjRpIkDw+PArc2tmzZUpL01FNPafHixUpMTNSZM2c0btw46z5Xr161hpannnrqhrl+\n+eUXubm5WVfXmjVrpsjIyFvWt2fPHqWlpWnevHmSJAcHByUmJsrb21tt27bViy++qIULF6pMmTKS\nJDs7O/Xp00cODg76+eeflZycbB2rcePG1nPLr8/T07NAYPL19ZUk1axZUxaLRYmJidb3Dhw4oPj4\neA0YMECSlJWVperVq8vLy0tVqlTRwIED9dxzz6ldu3ZycXG55XkBAB48hDAAQKFat26tL774Qt98\n8411m8ViKbBPdna29c/Xr1T9/rUxxvpnOzs76zaLxSInJyc5Ojpq6dKlhdbh6Oh4w7bf15E/1q04\nOTkpPDxcrq6uN7wXHx8vFxcXxcXFqUGDBtq3b5+ioqIUFRUlZ2dnDRs27Kbn9vvzznf9ytfv63Ny\nctITTzyhTz/99IbjVqxYoaNHj+rbb79Vt27d9MUXX8jd3f2W5wYAeLBwOyIA4KbGjh2rDz74QFlZ\nWZKkChUqKC4uTpKUmJioU6dO3fGY+Z+z2r9/v7y9veXi4qLq1atr586dkqQzZ85Yb1O8mUceeUSJ\niYmKjY21junj43PLYxo3bqxNmzZJkpKSkjR16lRJv62Q/fTTT1q+fLlmzZqlpKQkJSYmqlq1anJ2\ndtb58+f1ww8/WK/B7YqJibGej52dXYHw17BhQx06dEjx8fGSpE2bNmnbtm06fPiw1q1bp/r162vI\nkCGqX7++fvnllzuaFwBw/2MlDABwUzVq1FBgYKAiIiIk/XYr4aJFi9SjRw95eXlZbzm8Xfb29jp1\n6pQiIyOVnJysmTNnSpJmzJihKVOm6LPPPlNOTo7GjBlzy3HKli2rqVOn6s0335STk5OcnZ2toepm\nxo0bpwkTJujrr79WVlaWBg8erPT0dE2aNEnz58+Xu7u7XnrpJYWFhem9997T4sWL1bt3b9WqVUtD\nhw7VvHnz1Lx589s+15ycHA0ePFjnzp3T+PHjrSuA0m+3MY4bN06vvvqqypUrp7Jly2rGjBlydHTU\nvHnztHLlSjk5OalGjRqF3o4JAHiwWcz194gAAIA/LP+pkc8888y9LgUAcB/idkQAAAAAsCFWwgAA\nAADAhlgJAwAAAAAbIoQBAAAAgA0RwgAAAADAhghhAAAAAGBDhDAAAAAAsCFCGAAAAADY0P8HBXMv\ndsKDOGIAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f45b08934e0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"pd.DataFrame({'Train': [train.shape[0]], 'Test': [test.shape[0]]}).plot.barh(\n",
" figsize=(15, 2), legend='reverse', color=[\"black\",\"gold\"])\n",
"plt.title(\"Number of examples in each data set\")\n",
"plt.ylabel(\"Data sets\")\n",
"plt.yticks([])\n",
"plt.xlabel(\"Number of examples\");"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"_cell_guid": "9cee62f2-ed3c-4172-94c5-ea16ef5be423",
"_uuid": "e04875808daec5b695601f371a62dc16eda31de3"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Number of examples in train are 1438626.\n",
"Number of examples in test are 625134.\n"
]
}
],
"source": [
"print(\"Number of examples in train are %i.\" % train.shape[0])\n",
"print(\"Number of examples in test are %i.\" % test.shape[0])"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"_cell_guid": "2749314d-b984-4854-bd5e-968c2746f889",
"_uuid": "c609ceba07039c42ae78fd844658c7ffb1ed3f57"
},
"outputs": [
{
"data": {
"image/png": 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PH1ZkZKRycnKUnZ2td999Vw8//LDCw8PVoEEDHTp0SEuXLpXZbLb2kpCQoHnz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\nhAEAAACAgf4PpKaN6nabuxoAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f45b0808f98>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"pd.DataFrame({'Train': [train.shape[1]], 'Test': [test.shape[1]]}).plot.barh(\n",
" figsize=(15, 2), legend='reverse', color=[\"black\",\"gold\"])\n",
"plt.title(\"Number of columns in each data set\")\n",
"plt.ylabel(\"Data sets\")\n",
"plt.yticks([])\n",
"plt.xlabel(\"Number of columns\");"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "c750b3bd-57fa-4871-839e-df6e8e19b8ac",
"_uuid": "1fab314e2238b8e1747bbba971c44a8ad879cba0"
},
"source": [
"Ther are 11 columns in train and 9 in test as trip duration and dropoff datetime is not there in test.\n",
"Thanks to [Tuomas Tikkanen](https://www.kaggle.com/tuomastik) for colour code idea."
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"_cell_guid": "fef45182-c774-43e5-85a6-feec8b18a2f0",
"_uuid": "3075994acbf0d302af68aa23ada6b0511ff2363f"
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>vendor_id</th>\n",
" <th>passenger_count</th>\n",
" <th>pickup_longitude</th>\n",
" <th>pickup_latitude</th>\n",
" <th>dropoff_longitude</th>\n",
" <th>dropoff_latitude</th>\n",
" <th>trip_duration</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>1438626.00</td>\n",
" <td>1438626.00</td>\n",
" <td>1438626.00</td>\n",
" <td>1438626.00</td>\n",
" <td>1438626.00</td>\n",
" <td>1438626.00</td>\n",
" <td>1438626.00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>1.53</td>\n",
" <td>1.66</td>\n",
" <td>-73.97</td>\n",
" <td>40.75</td>\n",
" <td>-73.97</td>\n",
" <td>40.75</td>\n",
" <td>945.99</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>0.50</td>\n",
" <td>1.31</td>\n",
" <td>0.04</td>\n",
" <td>0.03</td>\n",
" <td>0.03</td>\n",
" <td>0.03</td>\n",
" <td>5252.16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>1.00</td>\n",
" <td>0.00</td>\n",
" <td>-74.03</td>\n",
" <td>40.63</td>\n",
" <td>-74.03</td>\n",
" <td>40.63</td>\n",
" <td>1.00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>1.00</td>\n",
" <td>1.00</td>\n",
" <td>-73.99</td>\n",
" <td>40.74</td>\n",
" <td>-73.99</td>\n",
" <td>40.74</td>\n",
" <td>394.00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>2.00</td>\n",
" <td>1.00</td>\n",
" <td>-73.98</td>\n",
" <td>40.75</td>\n",
" <td>-73.98</td>\n",
" <td>40.75</td>\n",
" <td>656.00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>2.00</td>\n",
" <td>2.00</td>\n",
" <td>-73.97</td>\n",
" <td>40.77</td>\n",
" <td>-73.96</td>\n",
" <td>40.77</td>\n",
" <td>1059.00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>max</th>\n",
" <td>2.00</td>\n",
" <td>6.00</td>\n",
" <td>-73.77</td>\n",
" <td>40.85</td>\n",
" <td>-73.77</td>\n",
" <td>40.85</td>\n",
" <td>3526282.00</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" vendor_id passenger_count pickup_longitude pickup_latitude \\\n",
"count 1438626.00 1438626.00 1438626.00 1438626.00 \n",
"mean 1.53 1.66 -73.97 40.75 \n",
"std 0.50 1.31 0.04 0.03 \n",
"min 1.00 0.00 -74.03 40.63 \n",
"25% 1.00 1.00 -73.99 40.74 \n",
"50% 2.00 1.00 -73.98 40.75 \n",
"75% 2.00 2.00 -73.97 40.77 \n",
"max 2.00 6.00 -73.77 40.85 \n",
"\n",
" dropoff_longitude dropoff_latitude trip_duration \n",
"count 1438626.00 1438626.00 1438626.00 \n",
"mean -73.97 40.75 945.99 \n",
"std 0.03 0.03 5252.16 \n",
"min -74.03 40.63 1.00 \n",
"25% -73.99 40.74 394.00 \n",
"50% -73.98 40.75 656.00 \n",
"75% -73.96 40.77 1059.00 \n",
"max -73.77 40.85 3526282.00 "
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pd.set_option('display.float_format', lambda x: '%.2f' % x)\n",
"train.describe()"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"_cell_guid": "7ea0482d-f833-4ede-bc24-a7607a742f51",
"_uuid": "9e1b13e45918eb54633120561e37828c709dc785",
"scrolled": true
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>vendor_id</th>\n",
" <th>passenger_count</th>\n",
" <th>pickup_longitude</th>\n",
" <th>pickup_latitude</th>\n",
" <th>dropoff_longitude</th>\n",
" <th>dropoff_latitude</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>625134.00</td>\n",
" <td>625134.00</td>\n",
" <td>625134.00</td>\n",
" <td>625134.00</td>\n",
" <td>625134.00</td>\n",
" <td>625134.00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>1.53</td>\n",
" <td>1.66</td>\n",
" <td>-73.97</td>\n",
" <td>40.75</td>\n",
" <td>-73.97</td>\n",
" <td>40.75</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>0.50</td>\n",
" <td>1.31</td>\n",
" <td>0.07</td>\n",
" <td>0.03</td>\n",
" <td>0.07</td>\n",
" <td>0.04</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>1.00</td>\n",
" <td>0.00</td>\n",
" <td>-121.93</td>\n",
" <td>37.39</td>\n",
" <td>-121.93</td>\n",
" <td>36.60</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>1.00</td>\n",
" <td>1.00</td>\n",
" <td>-73.99</td>\n",
" <td>40.74</td>\n",
" <td>-73.99</td>\n",
" <td>40.74</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>2.00</td>\n",
" <td>1.00</td>\n",
" <td>-73.98</td>\n",
" <td>40.75</td>\n",
" <td>-73.98</td>\n",
" <td>40.75</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>2.00</td>\n",
" <td>2.00</td>\n",
" <td>-73.97</td>\n",
" <td>40.77</td>\n",
" <td>-73.96</td>\n",
" <td>40.77</td>\n",
" </tr>\n",
" <tr>\n",
" <th>max</th>\n",
" <td>2.00</td>\n",
" <td>9.00</td>\n",
" <td>-69.25</td>\n",
" <td>42.81</td>\n",
" <td>-67.50</td>\n",
" <td>48.86</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" vendor_id passenger_count pickup_longitude pickup_latitude \\\n",
"count 625134.00 625134.00 625134.00 625134.00 \n",
"mean 1.53 1.66 -73.97 40.75 \n",
"std 0.50 1.31 0.07 0.03 \n",
"min 1.00 0.00 -121.93 37.39 \n",
"25% 1.00 1.00 -73.99 40.74 \n",
"50% 2.00 1.00 -73.98 40.75 \n",
"75% 2.00 2.00 -73.97 40.77 \n",
"max 2.00 9.00 -69.25 42.81 \n",
"\n",
" dropoff_longitude dropoff_latitude \n",
"count 625134.00 625134.00 \n",
"mean -73.97 40.75 \n",
"std 0.07 0.04 \n",
"min -121.93 36.60 \n",
"25% -73.99 40.74 \n",
"50% -73.98 40.75 \n",
"75% -73.96 40.77 \n",
"max -67.50 48.86 "
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"test.describe()"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "18268380-c131-4208-a58a-82410fad573e",
"_uuid": "4949a2f046568d581e2f1898d9d02874c6462170"
},
"source": [
"<a id='variables'></a>\n",
"\n",
"That's great. We have no missing value in any of the columns of train and test data as count value for all columns are same for both the data frames.\n",
"\n",
"## Analyze variables\n",
"\n",
"### Univariate analysis\n",
"\n",
"#### Target variable Trip duration\n",
"Lets plot trip duration.\n",
"Since the evaluation metircs is RMSLE.\n",
"We can log transform trip duration and use RMSE for training.\n",
"Dont forget to take exponential of it while submitting submission file."
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"_cell_guid": "951e54d2-82f6-40c3-bd27-c5d459f7593d",
"_uuid": "22115130be3b398c4903b19e683dcd7cc30c2e7d"
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/opt/conda/lib/python3.6/site-packages/matplotlib/axes/_axes.py:545: UserWarning: No labelled objects found. Use label='...' kwarg on individual plots.\n",
" warnings.warn(\"No labelled objects found. \"\n"
]
},
{
"data": {
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ATISADgAAAJgIAR0AAAAwEQI6AAAAYCIeXd0BAACATlNuaV022Oj8fgBXwAw6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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f45982fe198>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig, (ax1, ax2) = plt.subplots(1, 2,figsize=(12,8))\n",
"fig.suptitle('Train trip duration and log ot trip duration')\n",
"ax1.legend(loc=0)\n",
"ax1.set_ylabel('count')\n",
"ax1.set_xlabel('trip duration')\n",
"ax2.set_xlabel('log(trip duration)')\n",
"ax2.legend(loc=0)\n",
"ax1.hist(train.trip_duration,color='black')\n",
"train['log_trip_duration'] = np.log(train['trip_duration'].values)\n",
"ax2.hist(train.log_trip_duration,bins=50,color='gold');"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "277575b3-4ab8-4726-ace0-a8e5eba58a50",
"_uuid": "64e836be6715e146ea9cba53ef6d68ea149949ef"
},
"source": [
"#### Vendor ID"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"_cell_guid": "76562af9-e87e-4e40-bcb1-dac80c19b592",
"_uuid": "f57d4d7879b5a4d7aad36b606e0dd5fa37c864fb"
},
"outputs": [
{
"data": {
"image/png": 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Bx+MhKirKv2ygGiIiIhJYUM8ZaGpq4pFHHuHQoUPcfPPN+Hw+/3Of/P2TzmT8TGuIiIhI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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f45b07b7f60>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"train[\"vendor_id\"].value_counts().plot(kind='bar',color=[\"black\",\"gold\"])\n",
"plt.title(\"Vendors\")\n",
"plt.ylabel(\"Count for each Vender\")\n",
"plt.xlabel(\"Vendor Ids\");"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "8d172cc2-5422-4e40-97ef-c25cfd114541",
"_uuid": "42bcde0f9f5b511e560caeec0679c36d305dfda3",
"collapsed": true
},
"source": [
"#### Passenger Count in each ride"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"_cell_guid": "76251855-5ae9-4a75-bb30-b752eae421a3",
"_uuid": "7105226b6d703efb5bb6d5704e6a1ccbed79f25e"
},
"outputs": [
{
"data": {
"image/png": 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RUwoJIiIiYkohQUREREwpJIiIiIgphQQRERExpZAgIiIiphQSRERExJS7M3dWWFhIbGws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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f45eced6630>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"train[\"passenger_count\"].value_counts().plot(kind='bar',color=[\"black\",\"gold\"])\n",
"plt.title(\"Passengers in a group of\")\n",
"plt.ylabel(\"Count for each passenger\")\n",
"plt.xlabel(\"Number of Passengers\");"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "0a31e30b-f1c7-48ee-ab5d-ed6d5a590ec1",
"_uuid": "a5f98f455618585a0398545df9b566884aae09db"
},
"source": [
"Most popular choice of travel is single. and after that with 1 friend. and may be for long cars popular choice if travel is in group of 5 people. There are few trips with zero passengers. Those must be outliers and have to be removed.\n",
"\n",
"#### Store and Forward trip details"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"_cell_guid": "f9c35240-88a4-40e3-a929-f29ce3d05d03",
"_uuid": "6bb50876698052a2bc3ae6a3fc5926698c8eec10"
},
"outputs": [
{
"data": {
"image/png": 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cmTYLCd26ddPbb7+tzZs3a/PmzbLb7Vq3bp2io6N16NAhnT17VrW1tXI4HIqJidGoUaO0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\nQgIAADBFSAAAAKb+P9DjbmGgh1+GAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f4597fdeba8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"train[\"store_and_fwd_flag\"].value_counts().plot(kind='bar',color=[\"black\",\"gold\"])\n",
"plt.title(\"Store and Forward cases\")\n",
"plt.ylabel(\"Count for flags\")\n",
"plt.xlabel(\"Flag\");"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "70be5bfe-b841-416e-ab0e-70f3a0086d59",
"_uuid": "5c8bde19b87640d3cf10c7fa71d22c337817aec7"
},
"source": [
"Allmost all the journey details were immediately sent to vendors."
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"_cell_guid": "58ff5171-c553-48a0-8b41-b95c6e660001",
"_uuid": "6915e7fb58960e7bef1c40abe0d73d7f8d26b42e",
"collapsed": true
},
"outputs": [],
"source": [
"train['store_and_fwd_flag'] = 1 * (train.store_and_fwd_flag.values == 'Y')\n",
"test['store_and_fwd_flag'] = 1 * (test.store_and_fwd_flag.values == 'Y')"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "b56b8161-932a-4581-83d8-da28347e9145",
"_uuid": "4f1bb452dde0a64bc949bf5f8af5bf027071c7ec"
},
"source": [
"<a id='datetime'></a>\n",
"\n",
"## Feature engineering\n",
"\n",
"### DateTime features"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"_cell_guid": "31920daf-82a0-4faf-9e92-2310af3cac96",
"_uuid": "78bbe82d445dd310d398c44963f4df4706241741",
"collapsed": true
},
"outputs": [],
"source": [
"train['pickup_datetime'] = pd.to_datetime(train.pickup_datetime)\n",
"test['pickup_datetime'] = pd.to_datetime(test.pickup_datetime)\n",
"train['dropoff_datetime'] = pd.to_datetime(train.dropoff_datetime)\n",
"train['pickup_date'] = train['pickup_datetime'].dt.date\n",
"train['pickup_day'] = train['pickup_datetime'].dt.day\n",
"train['pickup_month'] = train['pickup_datetime'].dt.month\n",
"\n",
"test['pickup_date'] = test['pickup_datetime'].dt.date\n",
"test['pickup_day'] = test['pickup_datetime'].dt.day\n",
"test['pickup_month'] = test['pickup_datetime'].dt.month\n",
"\n",
"\n",
"train['pickup_weekday'] = train['pickup_datetime'].dt.weekday\n",
"train['pickup_weekofyear'] = train['pickup_datetime'].dt.weekofyear\n",
"train['pickup_hour'] = train['pickup_datetime'].dt.hour\n",
"train['pickup_minute'] = train['pickup_datetime'].dt.minute\n",
"train['pickup_dt'] = (train['pickup_datetime'] - train['pickup_datetime'].min()).dt.total_seconds()\n",
"train['pickup_week_hour'] = train['pickup_weekday'] * 24 + train['pickup_hour']\n",
"\n",
"test['pickup_weekday'] = test['pickup_datetime'].dt.weekday\n",
"test['pickup_weekofyear'] = test['pickup_datetime'].dt.weekofyear\n",
"test['pickup_hour'] = test['pickup_datetime'].dt.hour\n",
"test['pickup_minute'] = test['pickup_datetime'].dt.minute\n",
"test['pickup_dt'] = (test['pickup_datetime'] - train['pickup_datetime'].min()).dt.total_seconds()\n",
"test['pickup_week_hour'] = test['pickup_weekday'] * 24 + test['pickup_hour']"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "abc1c557-d670-4d31-b748-eb27bd32e51a",
"_uuid": "ff83124badc660648173366b7e4884d2cbde27bd"
},
"source": [
"Lets plot trip durations for each month"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"_cell_guid": "2392a82e-c18c-41d4-8c89-0a5b1af93171",
"_uuid": "bf52980c62b51f3440c9acaab72e10bddfe55b82"
},
"outputs": [
{
"data": {
"image/png": 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4R4PXKB7317/+Vd98841qampUW1vr/AMAAAAAOD+5XFH08/NTZmZmU9QCAAAA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\n41kKavTFRgAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f4597ef09b0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(15, 6)) \n",
"train.pickup_month.value_counts().plot(kind='bar',color=[\"black\",\"gold\"],align='center',width=0.3)\n",
"plt.xlabel(\"months\")\n",
"plt.ylabel(\"Number of trips\")\n",
"plt.title(\"Total trips in each month\");"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "533042be-61e3-4bef-afa5-e1c457143618",
"_uuid": "260f1083696077ee5837978c21abb35cec9fa513"
},
"source": [
"We have data from January to June of 2016. Highest number of trips happened in March and lowest in January."
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"_cell_guid": "d89fa1a4-a779-47a4-87ee-5ced6cb8983b",
"_uuid": "d10d3cc34108925ebe41ee2d4d7b6e0ef67b93cf"
},
"outputs": [
{
"data": {
"image/png": 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1a2e3bdbEmfvw3nvvVUxMjBITE3Xbbbepb9++6tixozw87P8nMC0t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\nqP8DZEcshJ0QooYAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f459828cfd0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(15, 6)) \n",
"train.pickup_day.value_counts().plot(kind='bar',color=[\"black\",\"gold\"],align='center',width=0.3)\n",
"plt.xlabel(\"Days\")\n",
"plt.ylabel(\"Number of trips\")\n",
"plt.title(\"Total trips on each day\");\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "b947d84e-4e24-4974-875d-c82ca93a7d9e",
"_uuid": "82d546f123610ac7c8daf87ea3d11a39247d2783"
},
"source": [
"Highest number of trips happened on 16th of the month while lowest on 31st. \n",
"30th and 31st have less trips because we have 6 months data and 30 and 31st came only 3 times each."
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"_cell_guid": "d0a7706e-784b-43e9-9d97-6e9a46a41b09",
"_uuid": "d4dbade5b494568a989080076649c1b2b5b2c56c"
},
"outputs": [
{
"data": {
"image/png": 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"text/plain": [
"<matplotlib.figure.Figure at 0x7f459808fac8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(15, 6)) \n",
"train.pickup_weekday.value_counts().plot(kind='bar',color=[\"black\",\"gold\"],align='center',width=0.3)\n",
"plt.xlabel(\"WeekDays\")\n",
"plt.ylabel(\"Number of trips\")\n",
"plt.title(\"Total trips on each weekday\");"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "2b5eebd3-8aa6-4dc5-8f7b-483a9585a172",
"_uuid": "263d5d7a67ad861e13e716ba0896b17fe856bcaf"
},
"source": [
"Highest number of trips happened on every Friday of the week while lowest on Mondays.(Monday blues :( ) "
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"_cell_guid": "d5efca1b-f9e1-4e1b-ba30-3d1426a3296a",
"_uuid": "8e106d73668fbe47a97ea33c473f94a0a8d16374"
},
"outputs": [
{
"data": {
"image/png": 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mzJljapaEhAQdPnxY//3f/61XXnlFc+bM0dChQ5Wdna0XX3zR1CxF\nRUXV/mzbts3ULNL510yTJk0UHh6upKQkJSUl2a/bvXu3qVm2bdumZcuW6dlnn631b+uDg4PVpUsX\nRUdHKyoqSlFRUdq2bZuioqIUHR1tahZXeo7ef/99++8vv/yyGjdurClTpqhVq1amf8ZI59/bxcXF\n+vHHHzVq1Cjl5+dr1KhRatasmenfDLtSFlf6nCkuLlbz5s0lSbfddpv9n4IuXbro7Nmzpmbx9PRU\nQECA7rjjDvn4+Cg4OFiS1LRpU9MLmCv9XZKkZ599Vjk5OZKkqVOnytvbW6NHj9Ztt92m8ePHm5rF\nZrOpQ4cOWrRokQYPHqwvvvhCvXv31oMPPqgnnnjC1CyGYVQpg9L50lpWVmZqlkWLFmnXrl06depU\nlZ+rvdmdI6WlpapXr54kydvbW82aNZMkNWzY0PQS5u7uroYNG8rNzU0PP/ywHn/8cY0YMUInT56U\nzWYzNYuXl5eaNGmisLAwBQQE2D9jbrrpJtWpU8fULKtXr1bnzp21a9cu9evXT6NHj9bNN9+s0aNH\nmz6iLKnSc9GgQQP73wV/f/+r+mUPI4SSCgsL9eSTT0qSevbsaf8n5N5779Xw4cNNzbJ3715NmzZN\nktSmTRs9+uijGjVqlO69914NGDDA1CzHjx/X66+/Xmnarbfeqg4dOmjo0KGmZunQoYMCAgIqTbPZ\nbDIMo1Y2jykpKdGQIUMkSbGxsRo3bpzeeustjR492vQP9QYNGmjmzJnau3evPvroI82YMUNt2rRR\ncHCwfH191bNnT9Oy/O1vf9O7776roUOHKjY2VpL08MMPa8WKFaZlqOBKz9GFcnJyNHfuXElSq1at\ntGbNGtMznDt3zr4e4uLi7GW5TZs2Sk1NtWwWV/qcufPOO/WXv/xFbdq00TfffKOOHTtKOv8l5e23\n325qlgYNGuj111/XqVOndOutt2rSpEmKiIjQtm3b5OfnZ2oWV/q7JEkFBQX2v83Hjh2zv7dDQkKU\nkpJiapYLP9dCQkLsW40cO3bMPppqltDQUI0cOVLdu3e3j5Lm5OQoNTVVd999t6lZkpKSNH36dE2c\nOFFeXl6VrsvMzDQ1y4gRI9S3b1+Fh4erYcOGevrpp9WuXTtlZmaa/j9e+/bt9eSTT2revHmqW7eu\nunfvrjp16ujRRx9Vbm6uqVn8/Pz0/vvva8SIEVq+fLmk8/sxfvDBB7r55ptNzVKnTh09//zz+u23\n3zRt2jS1a9dO5eXlpma40L///W8999xzMgxD+/bt05o1a9SzZ0998MEH8vb2vmr3QyHU+W9s9u3b\np5MnT+r06dPatm2b2rZtqz179qikpMTULIZh6Ntvv1VISIg2b96sunXrSpLp21BL5/8RSk1NVVRU\nlDw9PSWd/9Y6NTW1yoeqsyUkJOjEiRN6/vnnq1w3bNgwU7NIkoeHh9auXavY2Fi5ubnp1Vdf1Ysv\nvqiXXnpJZ86cMTVLxbdHLVq00OTJk1VSUqItW7Zo586d2rt3r6mFMCIiQh07dtSCBQuUkpKiCRMm\nmP5NYwUPDw+lpqaqR48etf4cnTp1yv4e9vLyUnZ2toKDg7V//34VFRWZmkX6/zulN23aVBMnTrRP\nz87ONv0zz5WyuNLnzNSpU7Vx40b9/vvveuSRR9SlSxdJ0vDhwxUUFGRqljlz5mjVqlUKCgpSr169\nlJKSou+++06BgYEaNWqUqVlsNpvWrVunyMjIWv+7JJ0vozNnztT999+vjh07as2aNerQoYO+/vpr\n+fv7m5qlT58+F50eEBBQ5YsOZ3vxxRe1ZcsWZWRkaMeOHfYco0ePVrt27UzNcuedd2rhwoUXHU2Z\nMGGCqVkeeOABdenSRenp6Tp48KAMw9BNN92kmTNnqnHjxqZmSUhIUGZmZqURuIiICLVr105ffvml\nqVlmz56tr776qtK0EydOqEmTJho7dqypWSq0bNlSCxcu1GeffWYfya0N8+bNq3Q5MDBQ0vkRwoov\noK4Gm8GhwrRlyxbNnj1bvr6+mjBhgqZPn65du3bJ399fU6dOVdu2bU3L8ttvv+m1117Tvn37FBQU\npISEBN18882aP3++unbtqjZt2piW5ciRI5o3b562bNmioqIiGYahevXqqVOnTnrqqad0yy23mJZF\nkj7//HN1797dvrlFhaSkJNP/KalYN1OmTKn0YZqSkqL58+dr/fr1pmV57rnnqnxgVMjLy5OPj49p\nWS60d+9ezZ49W3v37tW6detMz3L48GH7c1TxxYp0/jl69913tXr1atOy/HFTtj59+uiee+7Rs88+\nq/vvv18xMTGmZZGkn376ScnJyXrjjTfs0zZs2KD58+dr+vTppu6Pum3bNi1atOiiWV566SWFhYWZ\nlkU6f0CBHj166MYbb6w0feHChfYtSVB7Kj57f/jhB/uXKRV/l0aPHm168SktLdXHH3+sTZs2VfoH\nv0uXLurbt6/ppRAAroiBSxo2bFhtR7AzO8u6deuMbt26GXfffbeRkJBg5Ofn11qW9evXG926dTM6\nduxY61kM4/+vm4vlGTp0qOl5quMKr98jR44YhuEaWSqQpXq19TnjKu/t6rhSFlycqz1HrpYHAKrD\nJqNyrSNQuVKWC49AtXLlylo9AtXChQtd5mhY0qWPzmX2JpKu9Johy8W5UhbJtfK40pHuXGm94OJc\n7TlytTwAcCUohDp/BKpOnTpddFMTs49A5UpZKo5AJUkDBw6Ur6+vRowYoQULFpheei7M8vDDD8vP\nz6/WsjjKYzZXes2QxfWzuFoeV3pvu9J6wcW52nPkankA4IrU8gilS9i1a5cxbNgw49y5c1WuM3vz\nP1fKMmfOHOOJJ54wioqK7NO+/vpr4/777zciIiIsm8XV8rjSa4Ysrp/F1fLwXsLlcLXnyNXyAMCV\n4KAy/09RUZHq1KkjN7fKp2b85ZdfdNddd1k2S2Zmpu6+++5K39QXFBToyy+/1MCBAy2bxdXyuNJr\nhiyun8XV8vBewuVwtefI1fIAwOWiEAIAAACARbk5ngUAAAAAcD2iEAIAAACARVEIAQC4AgcOHFCX\nLl2qTA8KCuIIkwCAawaFEAAAAAAsikIIAMBVVl5erpdfflmDBg3SoEGD9MYbb0g6f0TV+Ph4+3wT\nJkzQJ598ogMHDuj+++/X2LFja+V8pgAA6+LE9AAAXGVffvmlDhw4oGXLlqm8vFyDBg1S586dL3mb\nPXv2aN68eWrZsqVJKQEAoBACAHDFTp48qWHDhlWZvmPHDnXq1Ek2m03u7u4KCwvTzp071bp162qX\n1aBBA8ogAMB0FEIAAK6Qr6+vFi9eXGlaUFCQPDwq/3k1DEM2m002m63S9JKSEvvvnp6ezgsKAEA1\n2IcQAICrrG3btkpPT5dhGCotLdUPP/yg0NBQ1a9fX0ePHpVhGCoqKtL27dtrOyoAwOIYIQQA4Crr\n3r27srKyFB8fr/LycnXv3l3/5//8H5WXlysoKEj9+vXTrbfeqnbt2tV2VACAxdkMwzBqOwQAAAAA\nwHxsMgoAAAAAFkUhBAAAAACLohACAAAAgEVRCAEAAADAoiiEAAAAAGBRFEIAAAAAsCgKIQAAAABY\n1P8FLfaBdXQyqpQAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f4597f35ba8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(15, 6)) \n",
"train.pickup_hour.value_counts().plot(kind='bar',color=[\"black\",\"gold\"],align='center',width=0.3)\n",
"plt.xlabel(\"Hour\")\n",
"plt.ylabel(\"Number of trips\")\n",
"plt.title(\"Total pickups at each hour\");"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "f40e78fd-a6c9-47de-a186-78788c7733fb",
"_uuid": "67f1d33dacb28546ad9df73d2774ff37b7bfa472"
},
"source": [
"Most pickups were at 6 O'Clock in the evening and least at 5 O'Clock early morning."
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"_cell_guid": "6b9f1578-7697-41c2-9b47-704bccc7e58d",
"_uuid": "9c0b8b824da5a840cda08c06bb5601314aca5b86"
},
"outputs": [
{
"data": {
"image/png": 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71V/0vPzyy9q2bZv8/Py0ZcsWTZo0Sa+88op8fX0tH11+4YUXtGrV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\nSUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f459808fbe0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"train['dropoff_hour'] = train['dropoff_datetime'].dt.hour\n",
"plt.figure(figsize=(15, 6)) \n",
"train.dropoff_hour.value_counts().plot(kind='bar',color=[\"black\",\"gold\"],align='center',width=0.3)\n",
"plt.xlabel(\"Hour\")\n",
"plt.ylabel(\"Number of trips\")\n",
"plt.title(\"Total dropoffs at each hour\");"
]
},
{
"cell_type": "markdown",
"metadata": {
"_cell_guid": "f3611958-5927-4e72-aa39-ba70cb2e2c30",
"_uuid": "2207baabd1669457762edb336e6ec4eb29bb2613"
},
"source": [
"Most dropoffs were at 7 O'Clock in the evening and least at 5 O'Clock early morning.\n",
"\n",
"### Bivariate analysis\n",
"\n",
"To be continued...\n",
"Please leave generous tip of upvote if you like it. :)"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"_cell_guid": "ec47b4e6-da7a-455b-ac00-b07821148076",
"_uuid": "b201c58e1230801023cb84f6a3c71aa3d7f13dd2",
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.1"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
| 0001/480/1480312.ipynb | s3://data-agents/kaggle-outputs/sharded/034_00001.jsonl.gz |
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