Description
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Create a Pandas DataFrame from List of Dicts
|
https://www.geeksforgeeks.org/create-a-pandas-dataframe-from-list-of-dicts/
|
import pandas as pd
# Initialise data to lists.
data = [
{"Geeks": "dataframe", "For": "using", "geeks": "list"},
{"Geeks": 10, "For": 20, "geeks": 30},
]
# With two column indices, values same
# as dictionary keys
df1 = pd.DataFrame(data, index=["ind1", "ind2"], columns=["Geeks", "For"])
# With two column indices with
# one index with other name
df2 = pd.DataFrame(data, index=["indx", "indy"])
# print for first data frame
print(df1, "\n")
# Print for second DataFrame.
print(df2)
|
#Output : Geeks For geeks
|
Create a Pandas DataFrame from List of Dicts
import pandas as pd
# Initialise data to lists.
data = [
{"Geeks": "dataframe", "For": "using", "geeks": "list"},
{"Geeks": 10, "For": 20, "geeks": 30},
]
# With two column indices, values same
# as dictionary keys
df1 = pd.DataFrame(data, index=["ind1", "ind2"], columns=["Geeks", "For"])
# With two column indices with
# one index with other name
df2 = pd.DataFrame(data, index=["indx", "indy"])
# print for first data frame
print(df1, "\n")
# Print for second DataFrame.
print(df2)
#Output : Geeks For geeks
[END]
|
Python | Convert list of nested dictionary into Pandas dataframe
|
https://www.geeksforgeeks.org/python-convert-list-of-nested-dictionary-into-pandas-dataframe/
|
# importing pandas
import pandas as pd
# List of nested dictionary initialization
list = [
{
"Student": [
{"Exam": 90, "Grade": "a"},
{"Exam": 99, "Grade": "b"},
{"Exam": 97, "Grade": "c"},
],
"Name": "Paras Jain",
},
{
"Student": [{"Exam": 89, "Grade": "a"}, {"Exam": 80, "Grade": "b"}],
"Name": "Chunky Pandey",
},
]
# print(list)
|
#Output : Name Maths Physics Chemistry
|
Python | Convert list of nested dictionary into Pandas dataframe
# importing pandas
import pandas as pd
# List of nested dictionary initialization
list = [
{
"Student": [
{"Exam": 90, "Grade": "a"},
{"Exam": 99, "Grade": "b"},
{"Exam": 97, "Grade": "c"},
],
"Name": "Paras Jain",
},
{
"Student": [{"Exam": 89, "Grade": "a"}, {"Exam": 80, "Grade": "b"}],
"Name": "Chunky Pandey",
},
]
# print(list)
#Output : Name Maths Physics Chemistry
[END]
|
Python | Convert list of nested dictionary into Pandas dataframe
|
https://www.geeksforgeeks.org/python-convert-list-of-nested-dictionary-into-pandas-dataframe/
|
# rows list initialization
rows = []
# appending rows
for data in list:
data_row = data["Student"]
time = data["Name"]
for row in data_row:
row["Name"] = time
rows.append(row)
# using data frame
df = pd.DataFrame(rows)
# print(df)
|
#Output : Name Maths Physics Chemistry
|
Python | Convert list of nested dictionary into Pandas dataframe
# rows list initialization
rows = []
# appending rows
for data in list:
data_row = data["Student"]
time = data["Name"]
for row in data_row:
row["Name"] = time
rows.append(row)
# using data frame
df = pd.DataFrame(rows)
# print(df)
#Output : Name Maths Physics Chemistry
[END]
|
Python | Convert list of nested dictionary into Pandas dataframe
|
https://www.geeksforgeeks.org/python-convert-list-of-nested-dictionary-into-pandas-dataframe/
|
# using pivot_table
df = df.pivot_table(index="Name", columns=["Grade"], values=["Exam"]).reset_index()
# Defining columns
df.columns = ["Name", "Maths", "Physics", "Chemistry"]
# print dataframe
print(df)
|
#Output : Name Maths Physics Chemistry
|
Python | Convert list of nested dictionary into Pandas dataframe
# using pivot_table
df = df.pivot_table(index="Name", columns=["Grade"], values=["Exam"]).reset_index()
# Defining columns
df.columns = ["Name", "Maths", "Physics", "Chemistry"]
# print dataframe
print(df)
#Output : Name Maths Physics Chemistry
[END]
|
Python | Convert list of nested dictionary into Pandas dataframe
|
https://www.geeksforgeeks.org/python-convert-list-of-nested-dictionary-into-pandas-dataframe/
|
# Python program to convert list of nested
# dictionary into Pandas dataframe
# importing pandas
import pandas as pd
# List of list of dictionary initialization
list = [
{
"Student": [
{"Exam": 90, "Grade": "a"},
{"Exam": 99, "Grade": "b"},
{"Exam": 97, "Grade": "c"},
],
"Name": "Paras Jain",
},
{
"Student": [{"Exam": 89, "Grade": "a"}, {"Exam": 80, "Grade": "b"}],
"Name": "Chunky Pandey",
},
]
# rows list initialization
rows = []
# appending rows
for data in list:
data_row = data["Student"]
time = data["Name"]
for row in data_row:
row["Name"] = time
rows.append(row)
# using data frame
df = pd.DataFrame(rows)
# using pivot_table
df = df.pivot_table(index="Name", columns=["Grade"], values=["Exam"]).reset_index()
# Defining columns
df.columns = ["Name", "Maths", "Physics", "Chemistry"]
# print dataframe
print(df)
|
#Output : Name Maths Physics Chemistry
|
Python | Convert list of nested dictionary into Pandas dataframe
# Python program to convert list of nested
# dictionary into Pandas dataframe
# importing pandas
import pandas as pd
# List of list of dictionary initialization
list = [
{
"Student": [
{"Exam": 90, "Grade": "a"},
{"Exam": 99, "Grade": "b"},
{"Exam": 97, "Grade": "c"},
],
"Name": "Paras Jain",
},
{
"Student": [{"Exam": 89, "Grade": "a"}, {"Exam": 80, "Grade": "b"}],
"Name": "Chunky Pandey",
},
]
# rows list initialization
rows = []
# appending rows
for data in list:
data_row = data["Student"]
time = data["Name"]
for row in data_row:
row["Name"] = time
rows.append(row)
# using data frame
df = pd.DataFrame(rows)
# using pivot_table
df = df.pivot_table(index="Name", columns=["Grade"], values=["Exam"]).reset_index()
# Defining columns
df.columns = ["Name", "Maths", "Physics", "Chemistry"]
# print dataframe
print(df)
#Output : Name Maths Physics Chemistry
[END]
|
Creating a dataframe from Pandas series
|
https://www.geeksforgeeks.org/creating-a-dataframe-from-pandas-series/
|
# importing pandas library
import pandas as pd
# Creating a list
author = ["Jitender", "Purnima", "Arpit", "Jyoti"]
# Creating a Series by passing list
# variable to Series() function
auth_series = pd.Series(author)
# Printing Series
print(auth_series)
|
#Output : 0 Jitender
|
Creating a dataframe from Pandas series
# importing pandas library
import pandas as pd
# Creating a list
author = ["Jitender", "Purnima", "Arpit", "Jyoti"]
# Creating a Series by passing list
# variable to Series() function
auth_series = pd.Series(author)
# Printing Series
print(auth_series)
#Output : 0 Jitender
[END]
|
Creating a dataframe from Pandas series
|
https://www.geeksforgeeks.org/creating-a-dataframe-from-pandas-series/
|
print(type(auth_series))
|
#Output : 0 Jitender
|
Creating a dataframe from Pandas series
print(type(auth_series))
#Output : 0 Jitender
[END]
|
Creating a dataframe from Pandas series
|
https://www.geeksforgeeks.org/creating-a-dataframe-from-pandas-series/
|
# Importing Pandas library
import pandas as pd
# Creating two lists
author = ["Jitender", "Purnima", "Arpit", "Jyoti"]
article = [210, 211, 114, 178]
# Creating two Series by passing lists
auth_series = pd.Series(author)
article_series = pd.Series(article)
# Creating a dictionary by passing Series objects as values
frame = {"Author": auth_series, "Article": article_series}
# Creating DataFrame by passing Dictionary
result = pd.DataFrame(frame)
# Printing elements of Dataframe
print(result)
|
#Output : 0 Jitender
|
Creating a dataframe from Pandas series
# Importing Pandas library
import pandas as pd
# Creating two lists
author = ["Jitender", "Purnima", "Arpit", "Jyoti"]
article = [210, 211, 114, 178]
# Creating two Series by passing lists
auth_series = pd.Series(author)
article_series = pd.Series(article)
# Creating a dictionary by passing Series objects as values
frame = {"Author": auth_series, "Article": article_series}
# Creating DataFrame by passing Dictionary
result = pd.DataFrame(frame)
# Printing elements of Dataframe
print(result)
#Output : 0 Jitender
[END]
|
Creating a dataframe from Pandas series
|
https://www.geeksforgeeks.org/creating-a-dataframe-from-pandas-series/
|
# Importing pandas library
import pandas as pd
# Creating Series
auth_series = pd.Series(["Jitender", "Purnima", "Arpit", "Jyoti"])
article_series = pd.Series([210, 211, 114, 178])
# Creating Dictionary
frame = {"Author": auth_series, "Article": article_series}
# Creating Dataframe
result = pd.DataFrame(frame)
# Creating another list
age = [21, 21, 24, 23]
# Creating new column in the dataframe by
# providing s Series created using list
result["Age"] = pd.Series(age)
# Printing dataframe
print(result)
|
#Output : 0 Jitender
|
Creating a dataframe from Pandas series
# Importing pandas library
import pandas as pd
# Creating Series
auth_series = pd.Series(["Jitender", "Purnima", "Arpit", "Jyoti"])
article_series = pd.Series([210, 211, 114, 178])
# Creating Dictionary
frame = {"Author": auth_series, "Article": article_series}
# Creating Dataframe
result = pd.DataFrame(frame)
# Creating another list
age = [21, 21, 24, 23]
# Creating new column in the dataframe by
# providing s Series created using list
result["Age"] = pd.Series(age)
# Printing dataframe
print(result)
#Output : 0 Jitender
[END]
|
Creating a dataframe from Pandas series
|
https://www.geeksforgeeks.org/creating-a-dataframe-from-pandas-series/
|
# Importing pandas library
import pandas as pd
# Creating Series
auth_series = pd.Series(["Jitender", "Purnima", "Arpit", "Jyoti"])
article_series = pd.Series([210, 211, 114, 178])
# Creating Dictionary
frame = {"Author": auth_series, "Article": article_series}
# Creating Dataframe
result = pd.DataFrame(frame)
# Creating another list
age = [21, 21, 24]
# Creating new column in the dataframe by
# providing s Series created using list
result["Age"] = pd.Series(age)
# Printing dataframe
print(result)
|
#Output : 0 Jitender
|
Creating a dataframe from Pandas series
# Importing pandas library
import pandas as pd
# Creating Series
auth_series = pd.Series(["Jitender", "Purnima", "Arpit", "Jyoti"])
article_series = pd.Series([210, 211, 114, 178])
# Creating Dictionary
frame = {"Author": auth_series, "Article": article_series}
# Creating Dataframe
result = pd.DataFrame(frame)
# Creating another list
age = [21, 21, 24]
# Creating new column in the dataframe by
# providing s Series created using list
result["Age"] = pd.Series(age)
# Printing dataframe
print(result)
#Output : 0 Jitender
[END]
|
Creating a dataframe from Pandas series
|
https://www.geeksforgeeks.org/creating-a-dataframe-from-pandas-series/
|
# Importing pandas library
import pandas as pd
# Creating dictionary of Series
dict1 = {
"Auth_Name": pd.Series(["Jitender", "Purnima", "Arpit", "Jyoti"]),
"Author_Book_No": pd.Series([210, 211, 114, 178]),
"Age": pd.Series([21, 21, 24, 23]),
}
# Creating Dataframe
df = pd.DataFrame(dict1)
# Printing dataframe
print(df)
|
#Output : 0 Jitender
|
Creating a dataframe from Pandas series
# Importing pandas library
import pandas as pd
# Creating dictionary of Series
dict1 = {
"Auth_Name": pd.Series(["Jitender", "Purnima", "Arpit", "Jyoti"]),
"Author_Book_No": pd.Series([210, 211, 114, 178]),
"Age": pd.Series([21, 21, 24, 23]),
}
# Creating Dataframe
df = pd.DataFrame(dict1)
# Printing dataframe
print(df)
#Output : 0 Jitender
[END]
|
Creating a dataframe from Pandas series
|
https://www.geeksforgeeks.org/creating-a-dataframe-from-pandas-series/
|
# Importing pandas library
import pandas as pd
# Creating dictionary of Series
dict1 = {
"Auth_Name": pd.Series(["Jitender", "Purnima", "Arpit", "Jyoti"]),
"Author_Book_No": pd.Series([210, 211, 114, 178]),
"Age": pd.Series([21, 21, 24, 23]),
}
# Creating Dataframe
df = pd.DataFrame(dict1, index=["SNo1", "SNo2", "SNo3", "SNo4"])
# Printing dataframe
print(df)
|
#Output : 0 Jitender
|
Creating a dataframe from Pandas series
# Importing pandas library
import pandas as pd
# Creating dictionary of Series
dict1 = {
"Auth_Name": pd.Series(["Jitender", "Purnima", "Arpit", "Jyoti"]),
"Author_Book_No": pd.Series([210, 211, 114, 178]),
"Age": pd.Series([21, 21, 24, 23]),
}
# Creating Dataframe
df = pd.DataFrame(dict1, index=["SNo1", "SNo2", "SNo3", "SNo4"])
# Printing dataframe
print(df)
#Output : 0 Jitender
[END]
|
Creating a dataframe from Pandas series
|
https://www.geeksforgeeks.org/creating-a-dataframe-from-pandas-series/
|
# This code is provided by Sheetal Verma
# Importing pandas library
import pandas as pd
# Creating dictionary of Series
dict1 = {
"Auth_Name": pd.Series(
["Jitender", "Purnima", "Arpit", "Jyoti"],
index=["SNo1", "SNo2", "SNo3", "SNo4"],
),
"Author_Book_No": pd.Series(
[210, 211, 114, 178], index=["SNo1", "SNo2", "SNo3", "SNo4"]
),
"Age": pd.Series([21, 21, 24, 23], index=["SNo1", "SNo2", "SNo3", "SNo4"]),
}
# Creating Dataframe
df = pd.DataFrame(dict1, index=["SNo1", "SNo2", "SNo3", "SNo4"])
# Printing dataframe
print(df)
|
#Output : 0 Jitender
|
Creating a dataframe from Pandas series
# This code is provided by Sheetal Verma
# Importing pandas library
import pandas as pd
# Creating dictionary of Series
dict1 = {
"Auth_Name": pd.Series(
["Jitender", "Purnima", "Arpit", "Jyoti"],
index=["SNo1", "SNo2", "SNo3", "SNo4"],
),
"Author_Book_No": pd.Series(
[210, 211, 114, 178], index=["SNo1", "SNo2", "SNo3", "SNo4"]
),
"Age": pd.Series([21, 21, 24, 23], index=["SNo1", "SNo2", "SNo3", "SNo4"]),
}
# Creating Dataframe
df = pd.DataFrame(dict1, index=["SNo1", "SNo2", "SNo3", "SNo4"])
# Printing dataframe
print(df)
#Output : 0 Jitender
[END]
|
Mapping external values to dataframe values in Pandas
|
https://www.geeksforgeeks.org/mapping-external-values-to-dataframe-values-in-pandas/
|
# Creating new dataframe
import pandas as pd
initial_data = {
"First_name": ["Ram", "Mohan", "Tina", "Jeetu", "Meera"],
"Last_name": ["Kumar", "Sharma", "Ali", "Gandhi", "Kumari"],
"Age": [42, 52, 36, 21, 23],
"City": ["Mumbai", "Noida", "Pune", "Delhi", "Bihar"],
}
df = pd.DataFrame(initial_data, columns=["First_name", "Last_name", "Age", "City"])
# Create new column using dictionary
new_data = {
"Ram": "B.Com",
"Mohan": "IAS",
"Tina": "LLB",
"Jeetu": "B.Tech",
"Meera": "MBBS",
}
# combine this new data with existing DataFrame
df["Qualification"] = df["First_name"].map(new_data)
print(df)
|
#Output :
|
Mapping external values to dataframe values in Pandas
# Creating new dataframe
import pandas as pd
initial_data = {
"First_name": ["Ram", "Mohan", "Tina", "Jeetu", "Meera"],
"Last_name": ["Kumar", "Sharma", "Ali", "Gandhi", "Kumari"],
"Age": [42, 52, 36, 21, 23],
"City": ["Mumbai", "Noida", "Pune", "Delhi", "Bihar"],
}
df = pd.DataFrame(initial_data, columns=["First_name", "Last_name", "Age", "City"])
# Create new column using dictionary
new_data = {
"Ram": "B.Com",
"Mohan": "IAS",
"Tina": "LLB",
"Jeetu": "B.Tech",
"Meera": "MBBS",
}
# combine this new data with existing DataFrame
df["Qualification"] = df["First_name"].map(new_data)
print(df)
#Output :
[END]
|
Mapping external values to dataframe values in Pandas
|
https://www.geeksforgeeks.org/mapping-external-values-to-dataframe-values-in-pandas/
|
# Creating new dataframe
import pandas as pd
initial_data = {
"First_name": ["Ram", "Mohan", "Tina", "Jeetu", "Meera"],
"Last_name": ["Kumar", "Sharma", "Ali", "Gandhi", "Kumari"],
"Age": [42, 52, 36, 21, 23],
"City": ["Mumbai", "Noida", "Pune", "Delhi", "Bihar"],
}
df = pd.DataFrame(initial_data, columns=["First_name", "Last_name", "Age", "City"])
# Create new column using dictionary
new_data = {"Ram": "Shyam", "Tina": "Riya", "Jeetu": "Jitender"}
print(df, end="\n\n")
# combine this new data with existing DataFrame
df = df.replace({"First_name": new_data})
print(df)
|
#Output :
|
Mapping external values to dataframe values in Pandas
# Creating new dataframe
import pandas as pd
initial_data = {
"First_name": ["Ram", "Mohan", "Tina", "Jeetu", "Meera"],
"Last_name": ["Kumar", "Sharma", "Ali", "Gandhi", "Kumari"],
"Age": [42, 52, 36, 21, 23],
"City": ["Mumbai", "Noida", "Pune", "Delhi", "Bihar"],
}
df = pd.DataFrame(initial_data, columns=["First_name", "Last_name", "Age", "City"])
# Create new column using dictionary
new_data = {"Ram": "Shyam", "Tina": "Riya", "Jeetu": "Jitender"}
print(df, end="\n\n")
# combine this new data with existing DataFrame
df = df.replace({"First_name": new_data})
print(df)
#Output :
[END]
|
Mapping external values to dataframe values in Pandas
|
https://www.geeksforgeeks.org/mapping-external-values-to-dataframe-values-in-pandas/
|
# Creating new dataframe
import pandas as pd
initial_data = {
"First_name": ["Ram", "Mohan", "Tina", "Jeetu", "Meera"],
"Last_name": ["Kumar", "Sharma", "Ali", "Gandhi", "Kumari"],
"Age": [42, 52, 36, 21, 23],
"City": ["Mumbai", "Noida", "Pune", "Delhi", "Bihar"],
}
df = pd.DataFrame(initial_data, columns=["First_name", "Last_name", "Age", "City"])
# Create new column using dictionary
new_data = {0: "Shyam", 2: "Riya", 3: "Jitender"}
# combine this new data with existing DataFrame
df["First_name"].update(pd.Series(new_data))
print(df)
|
#Output :
|
Mapping external values to dataframe values in Pandas
# Creating new dataframe
import pandas as pd
initial_data = {
"First_name": ["Ram", "Mohan", "Tina", "Jeetu", "Meera"],
"Last_name": ["Kumar", "Sharma", "Ali", "Gandhi", "Kumari"],
"Age": [42, 52, 36, 21, 23],
"City": ["Mumbai", "Noida", "Pune", "Delhi", "Bihar"],
}
df = pd.DataFrame(initial_data, columns=["First_name", "Last_name", "Age", "City"])
# Create new column using dictionary
new_data = {0: "Shyam", 2: "Riya", 3: "Jitender"}
# combine this new data with existing DataFrame
df["First_name"].update(pd.Series(new_data))
print(df)
#Output :
[END]
|
How to iterate over rows in Pandas Dataframe
|
https://www.geeksforgeeks.org/how-to-iterate-over-rows-in-pandas-dataframe/
|
# importing pandas
import pandas as pd
# list of dicts
input_df = [
{"name": "Sujeet", "age": 10},
{"name": "Sameer", "age": 11},
{"name": "Sumit", "age": 12},
]
df = pd.DataFrame(input_df)
print("Original DataFrame: \n", df)
print("\nRows iterated using iterrows() : ")
for index, row in df.iterrows():
print(row["name"], row["age"])
|
#Output : Original DataFrame:
|
How to iterate over rows in Pandas Dataframe
# importing pandas
import pandas as pd
# list of dicts
input_df = [
{"name": "Sujeet", "age": 10},
{"name": "Sameer", "age": 11},
{"name": "Sumit", "age": 12},
]
df = pd.DataFrame(input_df)
print("Original DataFrame: \n", df)
print("\nRows iterated using iterrows() : ")
for index, row in df.iterrows():
print(row["name"], row["age"])
#Output : Original DataFrame:
[END]
|
How to iterate over rows in Pandas Dataframe
|
https://www.geeksforgeeks.org/how-to-iterate-over-rows-in-pandas-dataframe/
|
# importing pandas
import pandas as pd
# list of dicts
input_df = [
{"name": "Sujeet", "age": 10},
{"name": "Sameer", "age": 110},
{"name": "Sumit", "age": 120},
]
df = pd.DataFrame(input_df)
print("Original DataFrame: \n", df)
print("\nRows iterated using itertuples() : ")
for row in df.itertuples():
print(getattr(row, "name"), getattr(row, "age"))
|
#Output : Original DataFrame:
|
How to iterate over rows in Pandas Dataframe
# importing pandas
import pandas as pd
# list of dicts
input_df = [
{"name": "Sujeet", "age": 10},
{"name": "Sameer", "age": 110},
{"name": "Sumit", "age": 120},
]
df = pd.DataFrame(input_df)
print("Original DataFrame: \n", df)
print("\nRows iterated using itertuples() : ")
for row in df.itertuples():
print(getattr(row, "name"), getattr(row, "age"))
#Output : Original DataFrame:
[END]
|
Different ways to iterate over rows in Pandas Dataframe
|
https://www.geeksforgeeks.org/different-ways-to-iterate-over-rows-in-pandas-dataframe/
|
# import pandas package as pd
import pandas as pd
# Define a dictionary containing students data
data = {
"Name": ["Ankit", "Amit", "Aishwarya", "Priyanka"],
"Age": [21, 19, 20, 18],
"Stream": ["Math", "Commerce", "Arts", "Biology"],
"Percentage": [88, 92, 95, 70],
}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data, columns=["Name", "Age", "Stream", "Percentage"])
print("Given Dataframe :\n", df)
print("\nIterating over rows using index attribute :\n")
# iterate through each row and select
# 'Name' and 'Stream' column respectively.
for ind in df.index:
print(df["Name"][ind], df["Stream"][ind])
|
#Output : Given Dataframe :
|
Different ways to iterate over rows in Pandas Dataframe
# import pandas package as pd
import pandas as pd
# Define a dictionary containing students data
data = {
"Name": ["Ankit", "Amit", "Aishwarya", "Priyanka"],
"Age": [21, 19, 20, 18],
"Stream": ["Math", "Commerce", "Arts", "Biology"],
"Percentage": [88, 92, 95, 70],
}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data, columns=["Name", "Age", "Stream", "Percentage"])
print("Given Dataframe :\n", df)
print("\nIterating over rows using index attribute :\n")
# iterate through each row and select
# 'Name' and 'Stream' column respectively.
for ind in df.index:
print(df["Name"][ind], df["Stream"][ind])
#Output : Given Dataframe :
[END]
|
Different ways to iterate over rows in Pandas Dataframe
|
https://www.geeksforgeeks.org/different-ways-to-iterate-over-rows-in-pandas-dataframe/
|
# import pandas package as pd
import pandas as pd
# Define a dictionary containing students data
data = {
"Name": ["Ankit", "Amit", "Aishwarya", "Priyanka"],
"Age": [21, 19, 20, 18],
"Stream": ["Math", "Commerce", "Arts", "Biology"],
"Percentage": [88, 92, 95, 70],
}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data, columns=["Name", "Age", "Stream", "Percentage"])
print("Given Dataframe :\n", df)
print("\nIterating over rows using loc function :\n")
# iterate through each row and select
# 'Name' and 'Age' column respectively.
for i in range(len(df)):
print(df.loc[i, "Name"], df.loc[i, "Age"])
|
#Output : Given Dataframe :
|
Different ways to iterate over rows in Pandas Dataframe
# import pandas package as pd
import pandas as pd
# Define a dictionary containing students data
data = {
"Name": ["Ankit", "Amit", "Aishwarya", "Priyanka"],
"Age": [21, 19, 20, 18],
"Stream": ["Math", "Commerce", "Arts", "Biology"],
"Percentage": [88, 92, 95, 70],
}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data, columns=["Name", "Age", "Stream", "Percentage"])
print("Given Dataframe :\n", df)
print("\nIterating over rows using loc function :\n")
# iterate through each row and select
# 'Name' and 'Age' column respectively.
for i in range(len(df)):
print(df.loc[i, "Name"], df.loc[i, "Age"])
#Output : Given Dataframe :
[END]
|
Different ways to iterate over rows in Pandas Dataframe
|
https://www.geeksforgeeks.org/different-ways-to-iterate-over-rows-in-pandas-dataframe/
|
# import pandas package as pd
import pandas as pd
# Define a dictionary containing students data
data = {
"Name": ["Ankit", "Amit", "Aishwarya", "Priyanka"],
"Age": [21, 19, 20, 18],
"Stream": ["Math", "Commerce", "Arts", "Biology"],
"Percentage": [88, 92, 95, 70],
}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data, columns=["Name", "Age", "Stream", "Percentage"])
print("Given Dataframe :\n", df)
print("\nIterating over rows using iloc function :\n")
# iterate through each row and select
# 0th and 2nd index column respectively.
for i in range(len(df)):
print(df.iloc[i, 0], df.iloc[i, 2])
|
#Output : Given Dataframe :
|
Different ways to iterate over rows in Pandas Dataframe
# import pandas package as pd
import pandas as pd
# Define a dictionary containing students data
data = {
"Name": ["Ankit", "Amit", "Aishwarya", "Priyanka"],
"Age": [21, 19, 20, 18],
"Stream": ["Math", "Commerce", "Arts", "Biology"],
"Percentage": [88, 92, 95, 70],
}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data, columns=["Name", "Age", "Stream", "Percentage"])
print("Given Dataframe :\n", df)
print("\nIterating over rows using iloc function :\n")
# iterate through each row and select
# 0th and 2nd index column respectively.
for i in range(len(df)):
print(df.iloc[i, 0], df.iloc[i, 2])
#Output : Given Dataframe :
[END]
|
Different ways to iterate over rows in Pandas Dataframe
|
https://www.geeksforgeeks.org/different-ways-to-iterate-over-rows-in-pandas-dataframe/
|
# import pandas package as pd
import pandas as pd
# Define a dictionary containing students data
data = {
"Name": ["Ankit", "Amit", "Aishwarya", "Priyanka"],
"Age": [21, 19, 20, 18],
"Stream": ["Math", "Commerce", "Arts", "Biology"],
"Percentage": [88, 92, 95, 70],
}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data, columns=["Name", "Age", "Stream", "Percentage"])
print("Given Dataframe :\n", df)
print("\nIterating over rows using iterrows() method :\n")
# iterate through each row and select
# 'Name' and 'Age' column respectively.
for index, row in df.iterrows():
print(row["Name"], row["Age"])
|
#Output : Given Dataframe :
|
Different ways to iterate over rows in Pandas Dataframe
# import pandas package as pd
import pandas as pd
# Define a dictionary containing students data
data = {
"Name": ["Ankit", "Amit", "Aishwarya", "Priyanka"],
"Age": [21, 19, 20, 18],
"Stream": ["Math", "Commerce", "Arts", "Biology"],
"Percentage": [88, 92, 95, 70],
}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data, columns=["Name", "Age", "Stream", "Percentage"])
print("Given Dataframe :\n", df)
print("\nIterating over rows using iterrows() method :\n")
# iterate through each row and select
# 'Name' and 'Age' column respectively.
for index, row in df.iterrows():
print(row["Name"], row["Age"])
#Output : Given Dataframe :
[END]
|
Different ways to iterate over rows in Pandas Dataframe
|
https://www.geeksforgeeks.org/different-ways-to-iterate-over-rows-in-pandas-dataframe/
|
# import pandas package as pd
import pandas as pd
# Define a dictionary containing students data
data = {
"Name": ["Ankit", "Amit", "Aishwarya", "Priyanka"],
"Age": [21, 19, 20, 18],
"Stream": ["Math", "Commerce", "Arts", "Biology"],
"Percentage": [88, 92, 95, 70],
}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data, columns=["Name", "Age", "Stream", "Percentage"])
print("Given Dataframe :\n", df)
print("\nIterating over rows using itertuples() method :\n")
# iterate through each row and select
# 'Name' and 'Percentage' column respectively.
for row in df.itertuples(index=True, name="Pandas"):
print(getattr(row, "Name"), getattr(row, "Percentage"))
|
#Output : Given Dataframe :
|
Different ways to iterate over rows in Pandas Dataframe
# import pandas package as pd
import pandas as pd
# Define a dictionary containing students data
data = {
"Name": ["Ankit", "Amit", "Aishwarya", "Priyanka"],
"Age": [21, 19, 20, 18],
"Stream": ["Math", "Commerce", "Arts", "Biology"],
"Percentage": [88, 92, 95, 70],
}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data, columns=["Name", "Age", "Stream", "Percentage"])
print("Given Dataframe :\n", df)
print("\nIterating over rows using itertuples() method :\n")
# iterate through each row and select
# 'Name' and 'Percentage' column respectively.
for row in df.itertuples(index=True, name="Pandas"):
print(getattr(row, "Name"), getattr(row, "Percentage"))
#Output : Given Dataframe :
[END]
|
Different ways to iterate over rows in Pandas Dataframe
|
https://www.geeksforgeeks.org/different-ways-to-iterate-over-rows-in-pandas-dataframe/
|
# import pandas package as pd
import pandas as pd
# Define a dictionary containing students data
data = {
"Name": ["Ankit", "Amit", "Aishwarya", "Priyanka"],
"Age": [21, 19, 20, 18],
"Stream": ["Math", "Commerce", "Arts", "Biology"],
"Percentage": [88, 92, 95, 70],
}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data, columns=["Name", "Age", "Stream", "Percentage"])
print("Given Dataframe :\n", df)
print("\nIterating over rows using apply function :\n")
# iterate through each row and concatenate
# 'Name' and 'Percentage' column respectively.
print(df.apply(lambda row: row["Name"] + " " + str(row["Percentage"]), axis=1))
|
#Output : Given Dataframe :
|
Different ways to iterate over rows in Pandas Dataframe
# import pandas package as pd
import pandas as pd
# Define a dictionary containing students data
data = {
"Name": ["Ankit", "Amit", "Aishwarya", "Priyanka"],
"Age": [21, 19, 20, 18],
"Stream": ["Math", "Commerce", "Arts", "Biology"],
"Percentage": [88, 92, 95, 70],
}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data, columns=["Name", "Age", "Stream", "Percentage"])
print("Given Dataframe :\n", df)
print("\nIterating over rows using apply function :\n")
# iterate through each row and concatenate
# 'Name' and 'Percentage' column respectively.
print(df.apply(lambda row: row["Name"] + " " + str(row["Percentage"]), axis=1))
#Output : Given Dataframe :
[END]
|
Selementsect any row from a Dataframe using iloc[] and iat[] in Pandas
|
https://www.geeksforgeeks.org/select-any-row-from-a-dataframe-using-iloc-and-iat-in-pandas/
|
import pandas as pd
# Create the dataframe
df = pd.DataFrame(
{
"Date": ["10/2/2011", "11/2/2011", "12/2/2011", "13/2/11"],
"Event": ["Music", "Poetry", "Theatre", "Comedy"],
"Cost": [10000, 5000, 15000, 2000],
}
)
# Create an empty list
Row_list = []
# Iterate over each row
for i in range((df.shape[0])):
# Using iloc to access the values of
# the current row denoted by "i"
Row_list.append(list(df.iloc[i, :]))
# Print the first 3 elements
print(Row_list[:3])
|
#Output : [[10000, '10/2/2011', 'Music'], [5000, '11/2/2011', 'Poetry'],
|
Selementsect any row from a Dataframe using iloc[] and iat[] in Pandas
import pandas as pd
# Create the dataframe
df = pd.DataFrame(
{
"Date": ["10/2/2011", "11/2/2011", "12/2/2011", "13/2/11"],
"Event": ["Music", "Poetry", "Theatre", "Comedy"],
"Cost": [10000, 5000, 15000, 2000],
}
)
# Create an empty list
Row_list = []
# Iterate over each row
for i in range((df.shape[0])):
# Using iloc to access the values of
# the current row denoted by "i"
Row_list.append(list(df.iloc[i, :]))
# Print the first 3 elements
print(Row_list[:3])
#Output : [[10000, '10/2/2011', 'Music'], [5000, '11/2/2011', 'Poetry'],
[END]
|
Selementsect any row from a Dataframe using iloc[] and iat[] in Pandas
|
https://www.geeksforgeeks.org/select-any-row-from-a-dataframe-using-iloc-and-iat-in-pandas/
|
# importing pandas as pd
import pandas as pd
# Create the dataframe
df = pd.DataFrame(
{
"Date": ["10/2/2011", "11/2/2011", "12/2/2011", "13/2/11"],
"Event": ["Music", "Poetry", "Theatre", "Comedy"],
"Cost": [10000, 5000, 15000, 2000],
}
)
# Create an empty list
Row_list = []
# Iterate over each row
for i in range((df.shape[0])):
# Create a list to store the data
# of the current row
cur_row = []
# iterate over all the columns
for j in range(df.shape[1]):
# append the data of each
# column to the list
cur_row.append(df.iat[i, j])
# append the current row to the list
Row_list.append(cur_row)
# Print the first 3 elements
print(Row_list[:3])
|
#Output : [[10000, '10/2/2011', 'Music'], [5000, '11/2/2011', 'Poetry'],
|
Selementsect any row from a Dataframe using iloc[] and iat[] in Pandas
# importing pandas as pd
import pandas as pd
# Create the dataframe
df = pd.DataFrame(
{
"Date": ["10/2/2011", "11/2/2011", "12/2/2011", "13/2/11"],
"Event": ["Music", "Poetry", "Theatre", "Comedy"],
"Cost": [10000, 5000, 15000, 2000],
}
)
# Create an empty list
Row_list = []
# Iterate over each row
for i in range((df.shape[0])):
# Create a list to store the data
# of the current row
cur_row = []
# iterate over all the columns
for j in range(df.shape[1]):
# append the data of each
# column to the list
cur_row.append(df.iat[i, j])
# append the current row to the list
Row_list.append(cur_row)
# Print the first 3 elements
print(Row_list[:3])
#Output : [[10000, '10/2/2011', 'Music'], [5000, '11/2/2011', 'Poetry'],
[END]
|
Limited rows selementsection with given column in Pandas | Python
|
https://www.geeksforgeeks.org/limited-rows-selection-with-given-column-in-pandas-python/
|
# Import pandas package
import pandas as pd
# Define a dictionary containing employee data
data = {
"Name": ["Jai", "Princi", "Gaurav", "Anuj"],
"Age": [27, 24, 22, 32],
"Address": ["Delhi", "Kanpur", "Allahabad", "Kannauj"],
"Qualification": ["Msc", "MA", "MCA", "Phd"],
}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data)
# select three rows and two columns
print(df.loc[1:3, ["Name", "Qualification"]])
|
#Output : Name Qualification
|
Limited rows selementsection with given column in Pandas | Python
# Import pandas package
import pandas as pd
# Define a dictionary containing employee data
data = {
"Name": ["Jai", "Princi", "Gaurav", "Anuj"],
"Age": [27, 24, 22, 32],
"Address": ["Delhi", "Kanpur", "Allahabad", "Kannauj"],
"Qualification": ["Msc", "MA", "MCA", "Phd"],
}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data)
# select three rows and two columns
print(df.loc[1:3, ["Name", "Qualification"]])
#Output : Name Qualification
[END]
|
Limited rows selementsection with given column in Pandas | Python
|
https://www.geeksforgeeks.org/limited-rows-selection-with-given-column-in-pandas-python/
|
# Import pandas package
import pandas as pd
# Define a dictionary containing employee data
data = {
"Name": ["Jai", "Princi", "Gaurav", "Anuj"],
"Age": [27, 24, 22, 32],
"Address": ["Delhi", "Kanpur", "Allahabad", "Kannauj"],
"Qualification": ["Msc", "MA", "MCA", "Phd"],
}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data)
# .loc DataFrame method
# filtering rows and selecting columns by label format
# df.loc[rows, columns]
# row 1, all columns
print(df.loc[0, :])
|
#Output : Name Qualification
|
Limited rows selementsection with given column in Pandas | Python
# Import pandas package
import pandas as pd
# Define a dictionary containing employee data
data = {
"Name": ["Jai", "Princi", "Gaurav", "Anuj"],
"Age": [27, 24, 22, 32],
"Address": ["Delhi", "Kanpur", "Allahabad", "Kannauj"],
"Qualification": ["Msc", "MA", "MCA", "Phd"],
}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data)
# .loc DataFrame method
# filtering rows and selecting columns by label format
# df.loc[rows, columns]
# row 1, all columns
print(df.loc[0, :])
#Output : Name Qualification
[END]
|
Limited rows selementsection with given column in Pandas | Python
|
https://www.geeksforgeeks.org/limited-rows-selection-with-given-column-in-pandas-python/
|
# Import pandas package
import pandas as pd
# Define a dictionary containing employee data
data = {
"Name": ["Jai", "Princi", "Gaurav", "Anuj"],
"Age": [27, 24, 22, 32],
"Address": ["Delhi", "Kanpur", "Allahabad", "Kannauj"],
"Qualification": ["Msc", "MA", "MCA", "Phd"],
}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data)
# iloc[row slicing, column slicing]
print(df.iloc[0:2, 1:3])
|
#Output : Name Qualification
|
Limited rows selementsection with given column in Pandas | Python
# Import pandas package
import pandas as pd
# Define a dictionary containing employee data
data = {
"Name": ["Jai", "Princi", "Gaurav", "Anuj"],
"Age": [27, 24, 22, 32],
"Address": ["Delhi", "Kanpur", "Allahabad", "Kannauj"],
"Qualification": ["Msc", "MA", "MCA", "Phd"],
}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data)
# iloc[row slicing, column slicing]
print(df.iloc[0:2, 1:3])
#Output : Name Qualification
[END]
|
Sorting rows in pandas DataFrame
|
https://www.geeksforgeeks.org/sorting-rows-in-pandas-dataframe/
|
# import modules
import pandas as pd
# create dataframe
data = {
"name": ["Simon", "Marsh", "Gaurav", "Alex", "Selena"],
"Maths": [8, 5, 6, 9, 7],
"Science": [7, 9, 5, 4, 7],
"English": [7, 4, 7, 6, 8],
}
df = pd.DataFrame(data)
# Sort the dataframe?????????s rows by Science,
# in descending order
a = df.sort_valu"Science", ascending=0)
print("Sorting rows by Science:\n \n", a)
|
#Output :
|
Sorting rows in pandas DataFrame
# import modules
import pandas as pd
# create dataframe
data = {
"name": ["Simon", "Marsh", "Gaurav", "Alex", "Selena"],
"Maths": [8, 5, 6, 9, 7],
"Science": [7, 9, 5, 4, 7],
"English": [7, 4, 7, 6, 8],
}
df = pd.DataFrame(data)
# Sort the dataframe?????????s rows by Science,
# in descending order
a = df.sort_valu"Science", ascending=0)
print("Sorting rows by Science:\n \n", a)
#Output :
[END]
|
Sorting rows in pandas DataFrame
|
https://www.geeksforgeeks.org/sorting-rows-in-pandas-dataframe/
|
# import modules
import pandas as pd
# create dataframe
data = {
"name": ["Simon", "Marsh", "Gaurav", "Alex", "Selena"],
"Maths": [8, 5, 6, 9, 7],
"Science": [7, 9, 5, 4, 7],
"English": [7, 4, 7, 6, 8],
}
df = pd.DataFrame(data)
# Sort the dataframe?????????s rows by Maths
# and then by English, in ascending order
b = df.sort_value"Maths", "English"])
print("Sort rows by Maths and then by English: \n\n", b)
|
#Output :
|
Sorting rows in pandas DataFrame
# import modules
import pandas as pd
# create dataframe
data = {
"name": ["Simon", "Marsh", "Gaurav", "Alex", "Selena"],
"Maths": [8, 5, 6, 9, 7],
"Science": [7, 9, 5, 4, 7],
"English": [7, 4, 7, 6, 8],
}
df = pd.DataFrame(data)
# Sort the dataframe?????????s rows by Maths
# and then by English, in ascending order
b = df.sort_value"Maths", "English"])
print("Sort rows by Maths and then by English: \n\n", b)
#Output :
[END]
|
Sorting rows in pandas DataFrame
|
https://www.geeksforgeeks.org/sorting-rows-in-pandas-dataframe/
|
import pandas as pd
# create dataframe
data = {
"name": ["Simon", "Marsh", "Gaurav", "Alex", "Selena"],
"Maths": [8, 5, 6, 9, 7],
"Science": [7, 9, 5, 4, 7],
"English": [7, 4, 7, 6, 8],
}
df = pd.DataFrame(data)
a = df.sort_values(by="Science", na_position="first")
print(a)
|
#Output :
|
Sorting rows in pandas DataFrame
import pandas as pd
# create dataframe
data = {
"name": ["Simon", "Marsh", "Gaurav", "Alex", "Selena"],
"Maths": [8, 5, 6, 9, 7],
"Science": [7, 9, 5, 4, 7],
"English": [7, 4, 7, 6, 8],
}
df = pd.DataFrame(data)
a = df.sort_values(by="Science", na_position="first")
print(a)
#Output :
[END]
|
Selementsect row with maximum and minimum value in Pandas dataframe
|
https://www.geeksforgeeks.org/select-row-with-maximum-and-minimum-value-in-pandas-dataframe/
|
# importing pandas and numpy
import pandas as pd
import numpy as np
# data of 2018 drivers world championship
dict1 = {
"Driver": [
"Hamilton",
"Vettel",
"Raikkonen",
"Verstappen",
"Bottas",
"Ricciardo",
"Hulkenberg",
"Perez",
"Magnussen",
"Sainz",
"Alonso",
"Ocon",
"Leclerc",
"Grosjean",
"Gasly",
"Vandoorne",
"Ericsson",
"Stroll",
"Hartley",
"Sirotkin",
],
"Points": [
408,
320,
251,
249,
247,
170,
69,
62,
56,
53,
50,
49,
39,
37,
29,
12,
9,
6,
4,
1,
],
"Age": [
33,
31,
39,
21,
29,
29,
31,
28,
26,
24,
37,
22,
21,
32,
22,
26,
28,
20,
29,
23,
],
}
# creating dataframe using DataFrame constructor
df = pd.DataFrame(dict1)
print(df.head(10))
|
#Output : 39
|
Selementsect row with maximum and minimum value in Pandas dataframe
# importing pandas and numpy
import pandas as pd
import numpy as np
# data of 2018 drivers world championship
dict1 = {
"Driver": [
"Hamilton",
"Vettel",
"Raikkonen",
"Verstappen",
"Bottas",
"Ricciardo",
"Hulkenberg",
"Perez",
"Magnussen",
"Sainz",
"Alonso",
"Ocon",
"Leclerc",
"Grosjean",
"Gasly",
"Vandoorne",
"Ericsson",
"Stroll",
"Hartley",
"Sirotkin",
],
"Points": [
408,
320,
251,
249,
247,
170,
69,
62,
56,
53,
50,
49,
39,
37,
29,
12,
9,
6,
4,
1,
],
"Age": [
33,
31,
39,
21,
29,
29,
31,
28,
26,
24,
37,
22,
21,
32,
22,
26,
28,
20,
29,
23,
],
}
# creating dataframe using DataFrame constructor
df = pd.DataFrame(dict1)
print(df.head(10))
#Output : 39
[END]
|
Selementsect row with maximum and minimum value in Pandas dataframe
|
https://www.geeksforgeeks.org/select-row-with-maximum-and-minimum-value-in-pandas-dataframe/
|
# creating dataframe using DataFrame constructor
df = pd.DataFrame(dict1)
# the result shows max on
# Driver, Points, Age columns.
print(df.max())
|
#Output : 39
|
Selementsect row with maximum and minimum value in Pandas dataframe
# creating dataframe using DataFrame constructor
df = pd.DataFrame(dict1)
# the result shows max on
# Driver, Points, Age columns.
print(df.max())
#Output : 39
[END]
|
Selementsect row with maximum and minimum value in Pandas dataframe
|
https://www.geeksforgeeks.org/select-row-with-maximum-and-minimum-value-in-pandas-dataframe/
|
# creating dataframe using DataFrame constructor
df = pd.DataFrame(dict1)
# Who scored more points ?
print(df[df.Points == df.Points.max()])
|
#Output : 39
|
Selementsect row with maximum and minimum value in Pandas dataframe
# creating dataframe using DataFrame constructor
df = pd.DataFrame(dict1)
# Who scored more points ?
print(df[df.Points == df.Points.max()])
#Output : 39
[END]
|
Selementsect row with maximum and minimum value in Pandas dataframe
|
https://www.geeksforgeeks.org/select-row-with-maximum-and-minimum-value-in-pandas-dataframe/
|
# creating dataframe using DataFrame constructor
df = pd.DataFrame(dict1)
# what is the maximum age ?
print(df.Age.max())
|
#Output : 39
|
Selementsect row with maximum and minimum value in Pandas dataframe
# creating dataframe using DataFrame constructor
df = pd.DataFrame(dict1)
# what is the maximum age ?
print(df.Age.max())
#Output : 39
[END]
|
Selementsect row with maximum and minimum value in Pandas dataframe
|
https://www.geeksforgeeks.org/select-row-with-maximum-and-minimum-value-in-pandas-dataframe/
|
# creating dataframe using DataFrame constructor
df = pd.DataFrame(dict1)
# Which row has maximum age |
# who is the oldest driver ?
print(df[df.Age == df.Age.max()])
|
#Output : 39
|
Selementsect row with maximum and minimum value in Pandas dataframe
# creating dataframe using DataFrame constructor
df = pd.DataFrame(dict1)
# Which row has maximum age |
# who is the oldest driver ?
print(df[df.Age == df.Age.max()])
#Output : 39
[END]
|
Selementsect row with maximum and minimum value in Pandas dataframe
|
https://www.geeksforgeeks.org/select-row-with-maximum-and-minimum-value-in-pandas-dataframe/
|
# creating dataframe using DataFrame constructor
df = pd.DataFrame(dict1)
# the result shows min on
# Driver, Points, Age columns.
print(df.min())
|
#Output : 39
|
Selementsect row with maximum and minimum value in Pandas dataframe
# creating dataframe using DataFrame constructor
df = pd.DataFrame(dict1)
# the result shows min on
# Driver, Points, Age columns.
print(df.min())
#Output : 39
[END]
|
Selementsect row with maximum and minimum value in Pandas dataframe
|
https://www.geeksforgeeks.org/select-row-with-maximum-and-minimum-value-in-pandas-dataframe/
|
# creating dataframe using DataFrame constructor
df = pd.DataFrame(dict1)
# Who scored less points ?
print(df[df.Points == df.Points.min()])
|
#Output : 39
|
Selementsect row with maximum and minimum value in Pandas dataframe
# creating dataframe using DataFrame constructor
df = pd.DataFrame(dict1)
# Who scored less points ?
print(df[df.Points == df.Points.min()])
#Output : 39
[END]
|
Selementsect row with maximum and minimum value in Pandas dataframe
|
https://www.geeksforgeeks.org/select-row-with-maximum-and-minimum-value-in-pandas-dataframe/
|
# creating dataframe using DataFrame constructor
df = pd.DataFrame(dict1)
# Which row has maximum age |
# who is the youngest driver ?
print(df[df.Age == df.Age.min()])
|
#Output : 39
|
Selementsect row with maximum and minimum value in Pandas dataframe
# creating dataframe using DataFrame constructor
df = pd.DataFrame(dict1)
# Which row has maximum age |
# who is the youngest driver ?
print(df[df.Age == df.Age.min()])
#Output : 39
[END]
|
Create a pandas column using for loop
|
https://www.geeksforgeeks.org/create-a-pandas-column-using-for-loop/
|
# importing libraries
import pandas as pd
import numpy as np
raw_Data = {
"Voter_name": [
"Geek1",
"Geek2",
"Geek3",
"Geek4",
"Geek5",
"Geek6",
"Geek7",
"Geek8",
],
"Voter_age": [15, 23, 25, 9, 67, 54, 42, np.NaN],
}
df = pd.DataFrame(raw_Data, columns=["Voter_name", "Voter_age"])
# //DataFrame will look like
#
# Voter_name Voter_age
# Geek1 15
# Geek2 23
# Geek3 25
# Geek4 09
# Geek5 67
# Geek6 54
# Geek7 42
# Geek8 not a number
eligible = []
# For each row in the column
for age in df["Voter_age"]:
if age >= 18: # if Voter eligible
eligible.append("Yes")
elif age < 18: # if voter is not eligible
eligible.append("No")
else:
eligible.append("Not Sure")
# Create a column from the list
df["Voter"] = eligible
print(df)
|
#Output :
|
Create a pandas column using for loop
# importing libraries
import pandas as pd
import numpy as np
raw_Data = {
"Voter_name": [
"Geek1",
"Geek2",
"Geek3",
"Geek4",
"Geek5",
"Geek6",
"Geek7",
"Geek8",
],
"Voter_age": [15, 23, 25, 9, 67, 54, 42, np.NaN],
}
df = pd.DataFrame(raw_Data, columns=["Voter_name", "Voter_age"])
# //DataFrame will look like
#
# Voter_name Voter_age
# Geek1 15
# Geek2 23
# Geek3 25
# Geek4 09
# Geek5 67
# Geek6 54
# Geek7 42
# Geek8 not a number
eligible = []
# For each row in the column
for age in df["Voter_age"]:
if age >= 18: # if Voter eligible
eligible.append("Yes")
elif age < 18: # if voter is not eligible
eligible.append("No")
else:
eligible.append("Not Sure")
# Create a column from the list
df["Voter"] = eligible
print(df)
#Output :
[END]
|
How to rename columns in Pandas DataFrame
|
https://www.geeksforgeeks.org/how-to-rename-columns-in-pandas-dataframe/
|
# Import pandas package
import pandas as pd
# Define a dictionary containing ICC rankings
rankings = {
"test": ["India", "South Africa", "England", "New Zealand", "Australia"],
"odi": ["England", "India", "New Zealand", "South Africa", "Pakistan"],
"t20": ["Pakistan", "India", "Australia", "England", "New Zealand"],
}
# Convert the dictionary into DataFrame
rankings_pd = pd.DataFrame(rankings)
# Before renaming the columns
print(rankings_pd)
rankings_pd.rename(columns={"test": "TEST"}, inplace=True)
# After renaming the columns
print("\nAfter modifying first column:\n", rankings_pd.columns)
|
#Output : col_test_1 col_odi_1 col_t20_1
|
How to rename columns in Pandas DataFrame
# Import pandas package
import pandas as pd
# Define a dictionary containing ICC rankings
rankings = {
"test": ["India", "South Africa", "England", "New Zealand", "Australia"],
"odi": ["England", "India", "New Zealand", "South Africa", "Pakistan"],
"t20": ["Pakistan", "India", "Australia", "England", "New Zealand"],
}
# Convert the dictionary into DataFrame
rankings_pd = pd.DataFrame(rankings)
# Before renaming the columns
print(rankings_pd)
rankings_pd.rename(columns={"test": "TEST"}, inplace=True)
# After renaming the columns
print("\nAfter modifying first column:\n", rankings_pd.columns)
#Output : col_test_1 col_odi_1 col_t20_1
[END]
|
How to rename columns in Pandas DataFrame
|
https://www.geeksforgeeks.org/how-to-rename-columns-in-pandas-dataframe/
|
# Import pandas package
import pandas as pd
# Define a dictionary containing ICC rankings
rankings = {
"test": ["India", "South Africa", "England", "New Zealand", "Australia"],
"odi": ["England", "India", "New Zealand", "South Africa", "Pakistan"],
"t20": ["Pakistan", "India", "Australia", "England", "New Zealand"],
}
# Convert the dictionary into DataFrame
rankings_pd = pd.DataFrame(rankings)
# Before renaming the columns
print(rankings_pd.columns)
rankings_pd.rename(columns={"test": "TEST", "odi": "ODI", "t20": "T20"}, inplace=True)
# After renaming the columns
print(rankings_pd.columns)
|
#Output : col_test_1 col_odi_1 col_t20_1
|
How to rename columns in Pandas DataFrame
# Import pandas package
import pandas as pd
# Define a dictionary containing ICC rankings
rankings = {
"test": ["India", "South Africa", "England", "New Zealand", "Australia"],
"odi": ["England", "India", "New Zealand", "South Africa", "Pakistan"],
"t20": ["Pakistan", "India", "Australia", "England", "New Zealand"],
}
# Convert the dictionary into DataFrame
rankings_pd = pd.DataFrame(rankings)
# Before renaming the columns
print(rankings_pd.columns)
rankings_pd.rename(columns={"test": "TEST", "odi": "ODI", "t20": "T20"}, inplace=True)
# After renaming the columns
print(rankings_pd.columns)
#Output : col_test_1 col_odi_1 col_t20_1
[END]
|
How to rename columns in Pandas DataFrame
|
https://www.geeksforgeeks.org/how-to-rename-columns-in-pandas-dataframe/
|
# Import pandas package
import pandas as pd
# Define a dictionary containing ICC rankings
rankings = {
"test": ["India", "South Africa", "England", "New Zealand", "Australia"],
"odi": ["England", "India", "New Zealand", "South Africa", "Pakistan"],
"t20": ["Pakistan", "India", "Australia", "England", "New Zealand"],
}
# Convert the dictionary into DataFrame
rankings_pd = pd.DataFrame(rankings)
# Before renaming the columns
print(rankings_pd.columns)
rankings_pd.columns = ["TEST", "ODI", "T-20"]
# After renaming the columns
print(rankings_pd.columns)
|
#Output : col_test_1 col_odi_1 col_t20_1
|
How to rename columns in Pandas DataFrame
# Import pandas package
import pandas as pd
# Define a dictionary containing ICC rankings
rankings = {
"test": ["India", "South Africa", "England", "New Zealand", "Australia"],
"odi": ["England", "India", "New Zealand", "South Africa", "Pakistan"],
"t20": ["Pakistan", "India", "Australia", "England", "New Zealand"],
}
# Convert the dictionary into DataFrame
rankings_pd = pd.DataFrame(rankings)
# Before renaming the columns
print(rankings_pd.columns)
rankings_pd.columns = ["TEST", "ODI", "T-20"]
# After renaming the columns
print(rankings_pd.columns)
#Output : col_test_1 col_odi_1 col_t20_1
[END]
|
How to rename columns in Pandas DataFrame
|
https://www.geeksforgeeks.org/how-to-rename-columns-in-pandas-dataframe/
|
# Import pandas package
import pandas as pd
# Define a dictionary containing ICC rankings
rankings = {
"test": ["India", "South Africa", "England", "New Zealand", "Australia"],
"odi": ["England", "India", "New Zealand", "South Africa", "Pakistan"],
"t20": ["Pakistan", "India", "Australia", "England", "New Zealand"],
}
# Convert the dictionary into DataFrame
rankings_pd = pd.DataFrame(rankings)
# Before renaming the columns
print(rankings_pd.columns)
rankings_pd.set_axis(["A", "B", "C"], axis="columns", inplace=True)
# After renaming the columns
print(rankings_pd.columns)
rankings_pd.head()
|
#Output : col_test_1 col_odi_1 col_t20_1
|
How to rename columns in Pandas DataFrame
# Import pandas package
import pandas as pd
# Define a dictionary containing ICC rankings
rankings = {
"test": ["India", "South Africa", "England", "New Zealand", "Australia"],
"odi": ["England", "India", "New Zealand", "South Africa", "Pakistan"],
"t20": ["Pakistan", "India", "Australia", "England", "New Zealand"],
}
# Convert the dictionary into DataFrame
rankings_pd = pd.DataFrame(rankings)
# Before renaming the columns
print(rankings_pd.columns)
rankings_pd.set_axis(["A", "B", "C"], axis="columns", inplace=True)
# After renaming the columns
print(rankings_pd.columns)
rankings_pd.head()
#Output : col_test_1 col_odi_1 col_t20_1
[END]
|
How to rename columns in Pandas DataFrame
|
https://www.geeksforgeeks.org/how-to-rename-columns-in-pandas-dataframe/
|
# Import pandas package
import pandas as pd
# Define a dictionary containing ICC rankings
rankings = {
"test": ["India", "South Africa", "England", "New Zealand", "Australia"],
"odi": ["England", "India", "New Zealand", "South Africa", "Pakistan"],
"t20": ["Pakistan", "India", "Australia", "England", "New Zealand"],
}
# Convert the dictionary into DataFrame
rankings_pd = pd.DataFrame(rankings)
# Before renaming the columns
print(rankings_pd.columns)
rankings_pd = rankings_pd.add_prefix("col_")
rankings_pd = rankings_pd.add_suffix("_1")
# After renaming the columns
rankings_pd.head()
|
#Output : col_test_1 col_odi_1 col_t20_1
|
How to rename columns in Pandas DataFrame
# Import pandas package
import pandas as pd
# Define a dictionary containing ICC rankings
rankings = {
"test": ["India", "South Africa", "England", "New Zealand", "Australia"],
"odi": ["England", "India", "New Zealand", "South Africa", "Pakistan"],
"t20": ["Pakistan", "India", "Australia", "England", "New Zealand"],
}
# Convert the dictionary into DataFrame
rankings_pd = pd.DataFrame(rankings)
# Before renaming the columns
print(rankings_pd.columns)
rankings_pd = rankings_pd.add_prefix("col_")
rankings_pd = rankings_pd.add_suffix("_1")
# After renaming the columns
rankings_pd.head()
#Output : col_test_1 col_odi_1 col_t20_1
[END]
|
How to rename columns in Pandas DataFrame
|
https://www.geeksforgeeks.org/how-to-rename-columns-in-pandas-dataframe/
|
# Import pandas package
import pandas as pd
# Define a dictionary containing ICC rankings
rankings = {
"test": ["India", "South Africa", "England", "New Zealand", "Australia"],
"odi": ["England", "India", "New Zealand", "South Africa", "Pakistan"],
"t20": ["Pakistan", "India", "Australia", "England", "New Zealand"],
}
# Convert the dictionary into DataFrame
rankings_pd = pd.DataFrame(rankings)
# Before renaming the columns
print(rankings_pd.columns)
# df = rankings_pd
rankings_pd.columns = rankings_pd.columns.str.replace("test", "Col_TEST")
rankings_pd.columns = rankings_pd.columns.str.replace("odi", "Col_ODI")
rankings_pd.columns = rankings_pd.columns.str.replace("t20", "Col_T20")
rankings_pd.head()
|
#Output : col_test_1 col_odi_1 col_t20_1
|
How to rename columns in Pandas DataFrame
# Import pandas package
import pandas as pd
# Define a dictionary containing ICC rankings
rankings = {
"test": ["India", "South Africa", "England", "New Zealand", "Australia"],
"odi": ["England", "India", "New Zealand", "South Africa", "Pakistan"],
"t20": ["Pakistan", "India", "Australia", "England", "New Zealand"],
}
# Convert the dictionary into DataFrame
rankings_pd = pd.DataFrame(rankings)
# Before renaming the columns
print(rankings_pd.columns)
# df = rankings_pd
rankings_pd.columns = rankings_pd.columns.str.replace("test", "Col_TEST")
rankings_pd.columns = rankings_pd.columns.str.replace("odi", "Col_ODI")
rankings_pd.columns = rankings_pd.columns.str.replace("t20", "Col_T20")
rankings_pd.head()
#Output : col_test_1 col_odi_1 col_t20_1
[END]
|
Split a column in Pandas dataframe and get part of it
|
https://www.geeksforgeeks.org/split-a-column-in-pandas-dataframe-and-get-part-of-it/
|
import pandas as pd
import numpy as np
df = pd.DataFrame(
{
"Geek_ID": ["Geek1_id", "Geek2_id", "Geek3_id", "Geek4_id", "Geek5_id"],
"Geek_A": [1, 1, 3, 2, 4],
"Geek_B": [1, 2, 3, 4, 6],
"Geek_R": np.random.randn(5),
}
)
# Geek_A Geek_B Geek_ID Geek_R
# 0 1 1 Geek1_id random number
# 1 1 2 Geek2_id random number
# 2 3 3 Geek3_id random number
# 3 2 4 Geek4_id random number
# 4 4 6 Geek5_id random number
print(df.Geek_ID.str.split("_").str[0])
|
#Output :
|
Split a column in Pandas dataframe and get part of it
import pandas as pd
import numpy as np
df = pd.DataFrame(
{
"Geek_ID": ["Geek1_id", "Geek2_id", "Geek3_id", "Geek4_id", "Geek5_id"],
"Geek_A": [1, 1, 3, 2, 4],
"Geek_B": [1, 2, 3, 4, 6],
"Geek_R": np.random.randn(5),
}
)
# Geek_A Geek_B Geek_ID Geek_R
# 0 1 1 Geek1_id random number
# 1 1 2 Geek2_id random number
# 2 3 3 Geek3_id random number
# 3 2 4 Geek4_id random number
# 4 4 6 Geek5_id random number
print(df.Geek_ID.str.split("_").str[0])
#Output :
[END]
|
Split a column in Pandas dataframe and get part of it
|
https://www.geeksforgeeks.org/split-a-column-in-pandas-dataframe-and-get-part-of-it/
|
import pandas as pd
import numpy as np
df = pd.DataFrame(
{
"Geek_ID": ["Geek1_id", "Geek2_id", "Geek3_id", "Geek4_id", "Geek5_id"],
"Geek_A": [1, 1, 3, 2, 4],
"Geek_B": [1, 2, 3, 4, 6],
"Geek_R": np.random.randn(5),
}
)
# Geek_A Geek_B Geek_ID Geek_R
# 0 1 1 Geek1_id random number
# 1 1 2 Geek2_id random number
# 2 3 3 Geek3_id random number
# 3 2 4 Geek4_id random number
# 4 4 6 Geek5_id random number
print(df.Geek_ID.str.split("_").str[0].tolist())
|
#Output :
|
Split a column in Pandas dataframe and get part of it
import pandas as pd
import numpy as np
df = pd.DataFrame(
{
"Geek_ID": ["Geek1_id", "Geek2_id", "Geek3_id", "Geek4_id", "Geek5_id"],
"Geek_A": [1, 1, 3, 2, 4],
"Geek_B": [1, 2, 3, 4, 6],
"Geek_R": np.random.randn(5),
}
)
# Geek_A Geek_B Geek_ID Geek_R
# 0 1 1 Geek1_id random number
# 1 1 2 Geek2_id random number
# 2 3 3 Geek3_id random number
# 3 2 4 Geek4_id random number
# 4 4 6 Geek5_id random number
print(df.Geek_ID.str.split("_").str[0].tolist())
#Output :
[END]
|
Split a column in Pandas dataframe and get part of it
|
https://www.geeksforgeeks.org/split-a-column-in-pandas-dataframe-and-get-part-of-it/
|
import pandas as pd
import numpy as np
df = pd.DataFrame(
{
"Geek_ID": ["Geek1_id", "Geek2_id", "Geek3_id", "Geek4_id", "Geek5_id"],
"Geek_A": [1, 1, 3, 2, 4],
"Geek_B": [1, 2, 3, 4, 6],
"Geek_R": np.random.randn(5),
}
)
# Geek_A Geek_B Geek_ID Geek_R
# 0 1 1 Geek1_id random number
# 1 1 2 Geek2_id random number
# 2 3 3 Geek3_id random number
# 3 2 4 Geek4_id random number
# 4 4 6 Geek5_id random number
print(df.Geek_ID.str.split("_").str[1].tolist())
|
#Output :
|
Split a column in Pandas dataframe and get part of it
import pandas as pd
import numpy as np
df = pd.DataFrame(
{
"Geek_ID": ["Geek1_id", "Geek2_id", "Geek3_id", "Geek4_id", "Geek5_id"],
"Geek_A": [1, 1, 3, 2, 4],
"Geek_B": [1, 2, 3, 4, 6],
"Geek_R": np.random.randn(5),
}
)
# Geek_A Geek_B Geek_ID Geek_R
# 0 1 1 Geek1_id random number
# 1 1 2 Geek2_id random number
# 2 3 3 Geek3_id random number
# 3 2 4 Geek4_id random number
# 4 4 6 Geek5_id random number
print(df.Geek_ID.str.split("_").str[1].tolist())
#Output :
[END]
|
Getting Unique values from a column in Pandas dataframe
|
https://www.geeksforgeeks.org/getting-unique-values-from-a-column-in-pandas-dataframe/
|
# import pandas as pd
import pandas as pd
gapminder_csv_url = "http://bit.ly/2cLzoxH"
# load the data with pd.read_csv
record = pd.read_csv(gapminder_csv_url)
record.head()
|
#Output :
|
Getting Unique values from a column in Pandas dataframe
# import pandas as pd
import pandas as pd
gapminder_csv_url = "http://bit.ly/2cLzoxH"
# load the data with pd.read_csv
record = pd.read_csv(gapminder_csv_url)
record.head()
#Output :
[END]
|
Getting Unique values from a column in Pandas dataframe
|
https://www.geeksforgeeks.org/getting-unique-values-from-a-column-in-pandas-dataframe/
|
# import pandas as pd
import pandas as pd
gapminder_csv_url = "http://bit.ly/2cLzoxH"
# load the data with pd.read_csv
record = pd.read_csv(gapminder_csv_url)
print(record["continent"].unique())
|
#Output :
|
Getting Unique values from a column in Pandas dataframe
# import pandas as pd
import pandas as pd
gapminder_csv_url = "http://bit.ly/2cLzoxH"
# load the data with pd.read_csv
record = pd.read_csv(gapminder_csv_url)
print(record["continent"].unique())
#Output :
[END]
|
Getting Unique values from a column in Pandas dataframe
|
https://www.geeksforgeeks.org/getting-unique-values-from-a-column-in-pandas-dataframe/
|
# import pandas as pd
import pandas as pd
gapminder_csv_url = "http://bit.ly/2cLzoxH"
# load the data with pd.read_csv
record = pd.read_csv(gapminder_csv_url)
print(record.country.unique())
|
#Output :
|
Getting Unique values from a column in Pandas dataframe
# import pandas as pd
import pandas as pd
gapminder_csv_url = "http://bit.ly/2cLzoxH"
# load the data with pd.read_csv
record = pd.read_csv(gapminder_csv_url)
print(record.country.unique())
#Output :
[END]
|
Getting Unique values from a column in Pandas dataframe
|
https://www.geeksforgeeks.org/getting-unique-values-from-a-column-in-pandas-dataframe/
|
# Write Python3 code here
# import pandas as pd
import pandas as pd
gapminder_csv_url = "http://bit.ly/2cLzoxH"
# load the data with pd.read_csv
record = pd.read_csv(gapminder_csv_url)
print(pd.unique(record["continent"]))
|
#Output :
|
Getting Unique values from a column in Pandas dataframe
# Write Python3 code here
# import pandas as pd
import pandas as pd
gapminder_csv_url = "http://bit.ly/2cLzoxH"
# load the data with pd.read_csv
record = pd.read_csv(gapminder_csv_url)
print(pd.unique(record["continent"]))
#Output :
[END]
|
Change Data Type for one or more columns in Pandas Dataframe
|
https://www.geeksforgeeks.org/change-data-type-for-one-or-more-columns-in-pandas-dataframe/
|
# importing pandas as pd
import pandas as pd
# sample dataframe
df = pd.DataFrame(
{
"A": [1, 2, 3, 4, 5],
"B": ["a", "b", "c", "d", "e"],
"C": [1.1, "1.0", "1.3", 2, 5],
}
)
# converting all columns to string type
df = df.astype(str)
print(df.dtypes)
|
#Output : Original_dtypes:
|
Change Data Type for one or more columns in Pandas Dataframe
# importing pandas as pd
import pandas as pd
# sample dataframe
df = pd.DataFrame(
{
"A": [1, 2, 3, 4, 5],
"B": ["a", "b", "c", "d", "e"],
"C": [1.1, "1.0", "1.3", 2, 5],
}
)
# converting all columns to string type
df = df.astype(str)
print(df.dtypes)
#Output : Original_dtypes:
[END]
|
Change Data Type for one or more columns in Pandas Dataframe
|
https://www.geeksforgeeks.org/change-data-type-for-one-or-more-columns-in-pandas-dataframe/
|
# importing pandas as pd
import pandas as pd
# sample dataframe
df = pd.DataFrame(
{
"A": [1, 2, 3, 4, 5],
"B": ["a", "b", "c", "d", "e"],
"C": [1.1, "1.0", "1.3", 2, 5],
}
)
# using dictionary to convert specific columns
convert_dict = {"A": int, "C": float}
df = df.astype(convert_dict)
print(df.dtypes)
|
#Output : Original_dtypes:
|
Change Data Type for one or more columns in Pandas Dataframe
# importing pandas as pd
import pandas as pd
# sample dataframe
df = pd.DataFrame(
{
"A": [1, 2, 3, 4, 5],
"B": ["a", "b", "c", "d", "e"],
"C": [1.1, "1.0", "1.3", 2, 5],
}
)
# using dictionary to convert specific columns
convert_dict = {"A": int, "C": float}
df = df.astype(convert_dict)
print(df.dtypes)
#Output : Original_dtypes:
[END]
|
Change Data Type for one or more columns in Pandas Dataframe
|
https://www.geeksforgeeks.org/change-data-type-for-one-or-more-columns-in-pandas-dataframe/
|
# importing pandas as pd
import pandas as pd
# sample dataframe
df = pd.DataFrame(
{
"A": [1, 2, 3, "4", "5"],
"B": ["a", "b", "c", "d", "e"],
"C": [1.1, "2.1", 3.0, "4.1", "5.1"],
}
)
# using apply method
df[["A", "C"]] = df[["A", "C"]].apply(pd.to_numeric)
print(df.dtypes)
|
#Output : Original_dtypes:
|
Change Data Type for one or more columns in Pandas Dataframe
# importing pandas as pd
import pandas as pd
# sample dataframe
df = pd.DataFrame(
{
"A": [1, 2, 3, "4", "5"],
"B": ["a", "b", "c", "d", "e"],
"C": [1.1, "2.1", 3.0, "4.1", "5.1"],
}
)
# using apply method
df[["A", "C"]] = df[["A", "C"]].apply(pd.to_numeric)
print(df.dtypes)
#Output : Original_dtypes:
[END]
|
Change Data Type for one or more columns in Pandas Dataframe
|
https://www.geeksforgeeks.org/change-data-type-for-one-or-more-columns-in-pandas-dataframe/
|
# importing pandas as pd
import pandas as pd
# sample dataframe
df = pd.DataFrame(
{
"A": [1, 2, 3, 4, 5],
"B": ["a", "b", "c", "d", "e"],
"C": [1.1, 2.1, 3.0, 4.1, 5.1],
},
dtype="object",
)
# converting datatypes
df = df.infer_objects()
print(df.dtypes)
|
#Output : Original_dtypes:
|
Change Data Type for one or more columns in Pandas Dataframe
# importing pandas as pd
import pandas as pd
# sample dataframe
df = pd.DataFrame(
{
"A": [1, 2, 3, 4, 5],
"B": ["a", "b", "c", "d", "e"],
"C": [1.1, 2.1, 3.0, 4.1, 5.1],
},
dtype="object",
)
# converting datatypes
df = df.infer_objects()
print(df.dtypes)
#Output : Original_dtypes:
[END]
|
Change Data Type for one or more columns in Pandas Dataframe
|
https://www.geeksforgeeks.org/change-data-type-for-one-or-more-columns-in-pandas-dataframe/
|
import pandas as pd
data = {"name": ["Aman", "Hardik", pd.NA], "qualified": [True, False, pd.NA]}
df = pd.DataFrame(data)
print("Original_dtypes:")
print(df.dtypes)
newdf = df.convert_dtypes()
print("New_dtypes:")
print(newdf.dtypes)
|
#Output : Original_dtypes:
|
Change Data Type for one or more columns in Pandas Dataframe
import pandas as pd
data = {"name": ["Aman", "Hardik", pd.NA], "qualified": [True, False, pd.NA]}
df = pd.DataFrame(data)
print("Original_dtypes:")
print(df.dtypes)
newdf = df.convert_dtypes()
print("New_dtypes:")
print(newdf.dtypes)
#Output : Original_dtypes:
[END]
|
Difference of two columns in Pandas dataframe
|
https://www.geeksforgeeks.org/difference-of-two-columns-in-pandas-dataframe/
|
import pandas as pd
# Create a DataFrame
df1 = {
"Name": ["George", "Andrea", "micheal", "maggie", "Ravi", "Xien", "Jalpa"],
"score1": [62, 47, 55, 74, 32, 77, 86],
"score2": [45, 78, 44, 89, 66, 49, 72],
}
df1 = pd.DataFrame(df1, columns=["Name", "score1", "score2"])
print("Given Dataframe :\n", df1)
# getting Difference
df1["Score_diff"] = df1["score1"] - df1["score2"]
print("\nDifference of score1 and score2 :\n", df1)
|
#Output :
|
Difference of two columns in Pandas dataframe
import pandas as pd
# Create a DataFrame
df1 = {
"Name": ["George", "Andrea", "micheal", "maggie", "Ravi", "Xien", "Jalpa"],
"score1": [62, 47, 55, 74, 32, 77, 86],
"score2": [45, 78, 44, 89, 66, 49, 72],
}
df1 = pd.DataFrame(df1, columns=["Name", "score1", "score2"])
print("Given Dataframe :\n", df1)
# getting Difference
df1["Score_diff"] = df1["score1"] - df1["score2"]
print("\nDifference of score1 and score2 :\n", df1)
#Output :
[END]
|
Difference of two columns in Pandas dataframe
|
https://www.geeksforgeeks.org/difference-of-two-columns-in-pandas-dataframe/
|
import pandas as pd
# Create a DataFrame
df1 = {
"Name": ["George", "Andrea", "micheal", "maggie", "Ravi", "Xien", "Jalpa"],
"score1": [62, 47, 55, 74, 32, 77, 86],
"score2": [45, 78, 44, 89, 66, 49, 72],
}
df1 = pd.DataFrame(df1, columns=["Name", "score1", "score2"])
print("Given Dataframe :\n", df1)
df1["Score_diff"] = df1["score1"].sub(df1["score2"], axis=0)
print("\nDifference of score1 and score2 :\n", df1)
|
#Output :
|
Difference of two columns in Pandas dataframe
import pandas as pd
# Create a DataFrame
df1 = {
"Name": ["George", "Andrea", "micheal", "maggie", "Ravi", "Xien", "Jalpa"],
"score1": [62, 47, 55, 74, 32, 77, 86],
"score2": [45, 78, 44, 89, 66, 49, 72],
}
df1 = pd.DataFrame(df1, columns=["Name", "score1", "score2"])
print("Given Dataframe :\n", df1)
df1["Score_diff"] = df1["score1"].sub(df1["score2"], axis=0)
print("\nDifference of score1 and score2 :\n", df1)
#Output :
[END]
|
How to drop one or multiple columns in Pandas Dataframe
|
https://www.geeksforgeeks.org/how-to-drop-one-or-multiple-columns-in-pandas-dataframe/
|
# Import pandas package
import pandas as pd
# create a dictionary with five fields each
data = {
"A": ["A1", "A2", "A3", "A4", "A5"],
"B": ["B1", "B2", "B3", "B4", "B5"],
"C": ["C1", "C2", "C3", "C4", "C5"],
"D": ["D1", "D2", "D3", "D4", "D5"],
"E": ["E1", "E2", "E3", "E4", "E5"],
}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data)
df
|
#Output : A C D E
|
How to drop one or multiple columns in Pandas Dataframe
# Import pandas package
import pandas as pd
# create a dictionary with five fields each
data = {
"A": ["A1", "A2", "A3", "A4", "A5"],
"B": ["B1", "B2", "B3", "B4", "B5"],
"C": ["C1", "C2", "C3", "C4", "C5"],
"D": ["D1", "D2", "D3", "D4", "D5"],
"E": ["E1", "E2", "E3", "E4", "E5"],
}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data)
df
#Output : A C D E
[END]
|
How to drop one or multiple columns in Pandas Dataframe
|
https://www.geeksforgeeks.org/how-to-drop-one-or-multiple-columns-in-pandas-dataframe/
|
# Import pandas package
import pandas as pd
# create a dictionary with five fields each
data = {
"A": ["A1", "A2", "A3", "A4", "A5"],
"B": ["B1", "B2", "B3", "B4", "B5"],
"C": ["C1", "C2", "C3", "C4", "C5"],
"D": ["D1", "D2", "D3", "D4", "D5"],
"E": ["E1", "E2", "E3", "E4", "E5"],
}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data)
# Remove column name 'A'
df.drop(["A"], axis=1)
|
#Output : A C D E
|
How to drop one or multiple columns in Pandas Dataframe
# Import pandas package
import pandas as pd
# create a dictionary with five fields each
data = {
"A": ["A1", "A2", "A3", "A4", "A5"],
"B": ["B1", "B2", "B3", "B4", "B5"],
"C": ["C1", "C2", "C3", "C4", "C5"],
"D": ["D1", "D2", "D3", "D4", "D5"],
"E": ["E1", "E2", "E3", "E4", "E5"],
}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data)
# Remove column name 'A'
df.drop(["A"], axis=1)
#Output : A C D E
[END]
|
How to drop one or multiple columns in Pandas Dataframe
|
https://www.geeksforgeeks.org/how-to-drop-one-or-multiple-columns-in-pandas-dataframe/
|
# Import pandas package
import pandas as pd
# create a dictionary with five fields each
data = {
"A": ["A1", "A2", "A3", "A4", "A5"],
"B": ["B1", "B2", "B3", "B4", "B5"],
"C": ["C1", "C2", "C3", "C4", "C5"],
"D": ["D1", "D2", "D3", "D4", "D5"],
"E": ["E1", "E2", "E3", "E4", "E5"],
}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data)
# Remove two columns name is 'C' and 'D'
df.drop(["C", "D"], axis=1)
# df.drop(columns =['C', 'D'])
|
#Output : A C D E
|
How to drop one or multiple columns in Pandas Dataframe
# Import pandas package
import pandas as pd
# create a dictionary with five fields each
data = {
"A": ["A1", "A2", "A3", "A4", "A5"],
"B": ["B1", "B2", "B3", "B4", "B5"],
"C": ["C1", "C2", "C3", "C4", "C5"],
"D": ["D1", "D2", "D3", "D4", "D5"],
"E": ["E1", "E2", "E3", "E4", "E5"],
}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data)
# Remove two columns name is 'C' and 'D'
df.drop(["C", "D"], axis=1)
# df.drop(columns =['C', 'D'])
#Output : A C D E
[END]
|
How to drop one or multiple columns in Pandas Dataframe
|
https://www.geeksforgeeks.org/how-to-drop-one-or-multiple-columns-in-pandas-dataframe/
|
# Import pandas package
import pandas as pd
# create a dictionary with five fields each
data = {
"A": ["A1", "A2", "A3", "A4", "A5"],
"B": ["B1", "B2", "B3", "B4", "B5"],
"C": ["C1", "C2", "C3", "C4", "C5"],
"D": ["D1", "D2", "D3", "D4", "D5"],
"E": ["E1", "E2", "E3", "E4", "E5"],
}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data)
# Remove three columns as index base
df.drop(df.columns[[0, 4, 2]], axis=1, inplace=True)
df
|
#Output : A C D E
|
How to drop one or multiple columns in Pandas Dataframe
# Import pandas package
import pandas as pd
# create a dictionary with five fields each
data = {
"A": ["A1", "A2", "A3", "A4", "A5"],
"B": ["B1", "B2", "B3", "B4", "B5"],
"C": ["C1", "C2", "C3", "C4", "C5"],
"D": ["D1", "D2", "D3", "D4", "D5"],
"E": ["E1", "E2", "E3", "E4", "E5"],
}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data)
# Remove three columns as index base
df.drop(df.columns[[0, 4, 2]], axis=1, inplace=True)
df
#Output : A C D E
[END]
|
How to drop one or multiple columns in Pandas Dataframe
|
https://www.geeksforgeeks.org/how-to-drop-one-or-multiple-columns-in-pandas-dataframe/
|
# Import pandas package
import pandas as pd
# create a dictionary with five fields each
data = {
"A": ["A1", "A2", "A3", "A4", "A5"],
"B": ["B1", "B2", "B3", "B4", "B5"],
"C": ["C1", "C2", "C3", "C4", "C5"],
"D": ["D1", "D2", "D3", "D4", "D5"],
"E": ["E1", "E2", "E3", "E4", "E5"],
}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data)
# Remove all columns between column index 1 to 3
df.drop(df.iloc[:, 1:3], inplace=True, axis=1)
df
|
#Output : A C D E
|
How to drop one or multiple columns in Pandas Dataframe
# Import pandas package
import pandas as pd
# create a dictionary with five fields each
data = {
"A": ["A1", "A2", "A3", "A4", "A5"],
"B": ["B1", "B2", "B3", "B4", "B5"],
"C": ["C1", "C2", "C3", "C4", "C5"],
"D": ["D1", "D2", "D3", "D4", "D5"],
"E": ["E1", "E2", "E3", "E4", "E5"],
}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data)
# Remove all columns between column index 1 to 3
df.drop(df.iloc[:, 1:3], inplace=True, axis=1)
df
#Output : A C D E
[END]
|
How to drop one or multiple columns in Pandas Dataframe
|
https://www.geeksforgeeks.org/how-to-drop-one-or-multiple-columns-in-pandas-dataframe/
|
# Import pandas package
import pandas as pd
# create a dictionary with five fields each
data = {
"A": ["A1", "A2", "A3", "A4", "A5"],
"B": ["B1", "B2", "B3", "B4", "B5"],
"C": ["C1", "C2", "C3", "C4", "C5"],
"D": ["D1", "D2", "D3", "D4", "D5"],
"E": ["E1", "E2", "E3", "E4", "E5"],
}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data)
# Remove all columns between column name 'B' to 'D'
df.drop(df.ix[:, "B":"D"].columns, axis=1)
|
#Output : A C D E
|
How to drop one or multiple columns in Pandas Dataframe
# Import pandas package
import pandas as pd
# create a dictionary with five fields each
data = {
"A": ["A1", "A2", "A3", "A4", "A5"],
"B": ["B1", "B2", "B3", "B4", "B5"],
"C": ["C1", "C2", "C3", "C4", "C5"],
"D": ["D1", "D2", "D3", "D4", "D5"],
"E": ["E1", "E2", "E3", "E4", "E5"],
}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data)
# Remove all columns between column name 'B' to 'D'
df.drop(df.ix[:, "B":"D"].columns, axis=1)
#Output : A C D E
[END]
|
How to drop one or multiple columns in Pandas Dataframe
|
https://www.geeksforgeeks.org/how-to-drop-one-or-multiple-columns-in-pandas-dataframe/
|
# Import pandas package
import pandas as pd
# create a dictionary with five fields each
data = {
"A": ["A1", "A2", "A3", "A4", "A5"],
"B": ["B1", "B2", "B3", "B4", "B5"],
"C": ["C1", "C2", "C3", "C4", "C5"],
"D": ["D1", "D2", "D3", "D4", "D5"],
"E": ["E1", "E2", "E3", "E4", "E5"],
}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data)
# Remove all columns between column name 'B' to 'D'
df.drop(df.loc[:, "B":"D"].columns, axis=1)
|
#Output : A C D E
|
How to drop one or multiple columns in Pandas Dataframe
# Import pandas package
import pandas as pd
# create a dictionary with five fields each
data = {
"A": ["A1", "A2", "A3", "A4", "A5"],
"B": ["B1", "B2", "B3", "B4", "B5"],
"C": ["C1", "C2", "C3", "C4", "C5"],
"D": ["D1", "D2", "D3", "D4", "D5"],
"E": ["E1", "E2", "E3", "E4", "E5"],
}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data)
# Remove all columns between column name 'B' to 'D'
df.drop(df.loc[:, "B":"D"].columns, axis=1)
#Output : A C D E
[END]
|
How to drop one or multiple columns in Pandas Dataframe
|
https://www.geeksforgeeks.org/how-to-drop-one-or-multiple-columns-in-pandas-dataframe/
|
# Import pandas package
import pandas as pd
# create a dictionary with five fields each
data = {
"A": ["A1", "A2", "A3", "A4", "A5"],
"B": ["B1", "B2", "B3", "B4", "B5"],
"C": ["C1", "C2", "C3", "C4", "C5"],
"D": ["D1", "D2", "D3", "D4", "D5"],
"E": ["E1", "E2", "E3", "E4", "E5"],
}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data)
for col in df.columns:
if "A" in col:
del df[col]
df
|
#Output : A C D E
|
How to drop one or multiple columns in Pandas Dataframe
# Import pandas package
import pandas as pd
# create a dictionary with five fields each
data = {
"A": ["A1", "A2", "A3", "A4", "A5"],
"B": ["B1", "B2", "B3", "B4", "B5"],
"C": ["C1", "C2", "C3", "C4", "C5"],
"D": ["D1", "D2", "D3", "D4", "D5"],
"E": ["E1", "E2", "E3", "E4", "E5"],
}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data)
for col in df.columns:
if "A" in col:
del df[col]
df
#Output : A C D E
[END]
|
How to drop one or multiple columns in Pandas Dataframe
|
https://www.geeksforgeeks.org/how-to-drop-one-or-multiple-columns-in-pandas-dataframe/
|
# Import pandas package
import pandas as pd
# create a dictionary with five fields each
data = {
"A": ["A1", "A2", "A3", "A4", "A5"],
"B": ["B1", "B2", "B3", "B4", "B5"],
"C": ["C1", "C2", "C3", "C4", "C5"],
"D": ["D1", "D2", "D3", "D4", "D5"],
"E": ["E1", "E2", "E3", "E4", "E5"],
}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data)
df.pop("B")
df
|
#Output : A C D E
|
How to drop one or multiple columns in Pandas Dataframe
# Import pandas package
import pandas as pd
# create a dictionary with five fields each
data = {
"A": ["A1", "A2", "A3", "A4", "A5"],
"B": ["B1", "B2", "B3", "B4", "B5"],
"C": ["C1", "C2", "C3", "C4", "C5"],
"D": ["D1", "D2", "D3", "D4", "D5"],
"E": ["E1", "E2", "E3", "E4", "E5"],
}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data)
df.pop("B")
df
#Output : A C D E
[END]
|
Create a Pandas Series from array
|
https://www.geeksforgeeks.org/create-a-pandas-series-from-array/
|
# importing Pandas & numpy
import pandas as pd
import numpy as np
# numpy array
data = np.array(["a", "b", "c", "d", "e"])
# creating series
s = pd.Series(data)
print(s)
|
#Output :
|
Create a Pandas Series from array
# importing Pandas & numpy
import pandas as pd
import numpy as np
# numpy array
data = np.array(["a", "b", "c", "d", "e"])
# creating series
s = pd.Series(data)
print(s)
#Output :
[END]
|
Create a Pandas Series from array
|
https://www.geeksforgeeks.org/create-a-pandas-series-from-array/
|
# importing Pandas & numpy
import pandas as pd
import numpy as np
# numpy array
data = np.array(["a", "b", "c", "d", "e"])
# creating series
s = pd.Series(data, index=[1000, 1001, 1002, 1003, 1004])
print(s)
|
#Output :
|
Create a Pandas Series from array
# importing Pandas & numpy
import pandas as pd
import numpy as np
# numpy array
data = np.array(["a", "b", "c", "d", "e"])
# creating series
s = pd.Series(data, index=[1000, 1001, 1002, 1003, 1004])
print(s)
#Output :
[END]
|
Creating a Pandas Series from Dictionary
|
https://www.geeksforgeeks.org/creating-a-pandas-series-from-dictionary/
|
# import the pandas lib as pd
import pandas as pd
# create a dictionary
dictionary = {"A": 10, "B": 20, "C": 30}
# create a series
series = pd.Series(dictionary)
print(series)
|
#Output : A 10
|
Creating a Pandas Series from Dictionary
# import the pandas lib as pd
import pandas as pd
# create a dictionary
dictionary = {"A": 10, "B": 20, "C": 30}
# create a series
series = pd.Series(dictionary)
print(series)
#Output : A 10
[END]
|
Creating a Pandas Series from Dictionary
|
https://www.geeksforgeeks.org/creating-a-pandas-series-from-dictionary/
|
# import the pandas lib as pd
import pandas as pd
# create a dictionary
dictionary = {"D": 10, "B": 20, "C": 30}
# create a series
series = pd.Series(dictionary)
print(series)
|
#Output : A 10
|
Creating a Pandas Series from Dictionary
# import the pandas lib as pd
import pandas as pd
# create a dictionary
dictionary = {"D": 10, "B": 20, "C": 30}
# create a series
series = pd.Series(dictionary)
print(series)
#Output : A 10
[END]
|
Creating a Pandas Series from Dictionary
|
https://www.geeksforgeeks.org/creating-a-pandas-series-from-dictionary/
|
# import the pandas lib as pd
import pandas as pd
# create a dictionary
dictionary = {"A": 50, "B": 10, "C": 80}
# create a series
series = pd.Series(dictionary, index=["B", "C", "A"])
print(series)
|
#Output : A 10
|
Creating a Pandas Series from Dictionary
# import the pandas lib as pd
import pandas as pd
# create a dictionary
dictionary = {"A": 50, "B": 10, "C": 80}
# create a series
series = pd.Series(dictionary, index=["B", "C", "A"])
print(series)
#Output : A 10
[END]
|
Creating a Pandas Series from Dictionary
|
https://www.geeksforgeeks.org/creating-a-pandas-series-from-dictionary/
|
# import the pandas lib as pd
import pandas as pd
# create a dictionary
dictionary = {"A": 50, "B": 10, "C": 80}
# create a series
series = pd.Series(dictionary, index=["B", "C", "D", "A"])
print(series)
|
#Output : A 10
|
Creating a Pandas Series from Dictionary
# import the pandas lib as pd
import pandas as pd
# create a dictionary
dictionary = {"A": 50, "B": 10, "C": 80}
# create a series
series = pd.Series(dictionary, index=["B", "C", "D", "A"])
print(series)
#Output : A 10
[END]
|
Pandas | Basic of Time Series Manipulation
|
https://www.geeksforgeeks.org/pandas-basic-of-time-series-manipulation/
|
import pandas as pd
from datetime import datetime
import numpy as np
range_date = pd.date_range(start="1/1/2019", end="1/08/2019", freq="Min")
print(range_date)
|
#Output : DatetimeIndex(['2019-01-01 00:00:00', '2019-01-01 00:01:00',
|
Pandas | Basic of Time Series Manipulation
import pandas as pd
from datetime import datetime
import numpy as np
range_date = pd.date_range(start="1/1/2019", end="1/08/2019", freq="Min")
print(range_date)
#Output : DatetimeIndex(['2019-01-01 00:00:00', '2019-01-01 00:01:00',
[END]
|
Pandas | Basic of Time Series Manipulation
|
https://www.geeksforgeeks.org/pandas-basic-of-time-series-manipulation/
|
import pandas as pd
from datetime import datetime
import numpy as np
range_date = pd.date_range(start="1/1/2019", end="1/08/2019", freq="Min")
print(type(range_date[110]))
|
#Output : DatetimeIndex(['2019-01-01 00:00:00', '2019-01-01 00:01:00',
|
Pandas | Basic of Time Series Manipulation
import pandas as pd
from datetime import datetime
import numpy as np
range_date = pd.date_range(start="1/1/2019", end="1/08/2019", freq="Min")
print(type(range_date[110]))
#Output : DatetimeIndex(['2019-01-01 00:00:00', '2019-01-01 00:01:00',
[END]
|
Pandas | Basic of Time Series Manipulation
|
https://www.geeksforgeeks.org/pandas-basic-of-time-series-manipulation/
|
import pandas as pd
from datetime import datetime
import numpy as np
range_date = pd.date_range(start="1/1/2019", end="1/08/2019", freq="Min")
df = pd.DataFrame(range_date, columns=["date"])
df["data"] = np.random.randint(0, 100, size=(len(range_date)))
print(df.head(10))
|
#Output : DatetimeIndex(['2019-01-01 00:00:00', '2019-01-01 00:01:00',
|
Pandas | Basic of Time Series Manipulation
import pandas as pd
from datetime import datetime
import numpy as np
range_date = pd.date_range(start="1/1/2019", end="1/08/2019", freq="Min")
df = pd.DataFrame(range_date, columns=["date"])
df["data"] = np.random.randint(0, 100, size=(len(range_date)))
print(df.head(10))
#Output : DatetimeIndex(['2019-01-01 00:00:00', '2019-01-01 00:01:00',
[END]
|
Pandas | Basic of Time Series Manipulation
|
https://www.geeksforgeeks.org/pandas-basic-of-time-series-manipulation/
|
import pandas as pd
from datetime import datetime
import numpy as np
range_date = pd.date_range(start="1/1/2019", end="1/08/2019", freq="Min")
df = pd.DataFrame(range_date, columns=["date"])
df["data"] = np.random.randint(0, 100, size=(len(range_date)))
string_data = [str(x) for x in range_date]
print(string_data[1:11])
|
#Output : DatetimeIndex(['2019-01-01 00:00:00', '2019-01-01 00:01:00',
|
Pandas | Basic of Time Series Manipulation
import pandas as pd
from datetime import datetime
import numpy as np
range_date = pd.date_range(start="1/1/2019", end="1/08/2019", freq="Min")
df = pd.DataFrame(range_date, columns=["date"])
df["data"] = np.random.randint(0, 100, size=(len(range_date)))
string_data = [str(x) for x in range_date]
print(string_data[1:11])
#Output : DatetimeIndex(['2019-01-01 00:00:00', '2019-01-01 00:01:00',
[END]
|
Pandas | Basic of Time Series Manipulation
|
https://www.geeksforgeeks.org/pandas-basic-of-time-series-manipulation/
|
import pandas as pd
from datetime import datetime
import numpy as np
range_data = pd.date_range(start="1/1/2019", end="1/08/2019", freq="Min")
df = pd.DataFrame(range_data, columns=["date"])
df["data"] = np.random.randint(0, 100, size=(len(range_data)))
df["datetime"] = pd.to_datetime(df["date"])
df = df.set_index("datetime")
df.drop(["date"], axis=1, inplace=True)
print(df["2019-01-05"][1:11])
|
#Output : DatetimeIndex(['2019-01-01 00:00:00', '2019-01-01 00:01:00',
|
Pandas | Basic of Time Series Manipulation
import pandas as pd
from datetime import datetime
import numpy as np
range_data = pd.date_range(start="1/1/2019", end="1/08/2019", freq="Min")
df = pd.DataFrame(range_data, columns=["date"])
df["data"] = np.random.randint(0, 100, size=(len(range_data)))
df["datetime"] = pd.to_datetime(df["date"])
df = df.set_index("datetime")
df.drop(["date"], axis=1, inplace=True)
print(df["2019-01-05"][1:11])
#Output : DatetimeIndex(['2019-01-01 00:00:00', '2019-01-01 00:01:00',
[END]
|
Read More
|
https://www.geeksforgeeks.org/how-to-get-the-daily-news-using-python/
|
import requests
from bs4 import BeautifulSoup
|
#Output : pip install bs4
|
Read More
import requests
from bs4 import BeautifulSoup
#Output : pip install bs4
[END]
|
Read More
|
https://www.geeksforgeeks.org/how-to-get-the-daily-news-using-python/
|
url = "https://www.bbc.com/news"
response = requests.get(url)
|
#Output : pip install bs4
|
Read More
url = "https://www.bbc.com/news"
response = requests.get(url)
#Output : pip install bs4
[END]
|
Read More
|
https://www.geeksforgeeks.org/how-to-get-the-daily-news-using-python/
|
soup = BeautifulSoup(response.text, "html.parser")
headlines = soup.find("body").find_all("h3")
for x in headlines:
print(x.text.strip())
|
#Output : pip install bs4
|
Read More
soup = BeautifulSoup(response.text, "html.parser")
headlines = soup.find("body").find_all("h3")
for x in headlines:
print(x.text.strip())
#Output : pip install bs4
[END]
|
Read More
|
https://www.geeksforgeeks.org/how-to-get-the-daily-news-using-python/
|
import requests
from bs4 import BeautifulSoup
url = "https://www.bbc.com/news"
response = requests.get(url)
soup = BeautifulSoup(response.text, "html.parser")
headlines = soup.find("body").find_all("h3")
for x in headlines:
print(x.text.strip())
|
#Output : pip install bs4
|
Read More
import requests
from bs4 import BeautifulSoup
url = "https://www.bbc.com/news"
response = requests.get(url)
soup = BeautifulSoup(response.text, "html.parser")
headlines = soup.find("body").find_all("h3")
for x in headlines:
print(x.text.strip())
#Output : pip install bs4
[END]
|
Read More
|
https://www.geeksforgeeks.org/how-to-get-the-daily-news-using-python/
|
import requests
from bs4 import BeautifulSoup
url = "https://www.bbc.com/news"
response = requests.get(url)
soup = BeautifulSoup(response.text, "html.parser")
headlines = soup.find("body").find_all("h3")
unwanted = [
"BBC World News TV",
"BBC World Service Radio",
"News daily newsletter",
"Mobile app",
"Get in touch",
]
for x in list(dict.fromkeys(headlines)):
if x.text.strip() not in unwanted:
print(x.text.strip())
|
#Output : pip install bs4
|
Read More
import requests
from bs4 import BeautifulSoup
url = "https://www.bbc.com/news"
response = requests.get(url)
soup = BeautifulSoup(response.text, "html.parser")
headlines = soup.find("body").find_all("h3")
unwanted = [
"BBC World News TV",
"BBC World Service Radio",
"News daily newsletter",
"Mobile app",
"Get in touch",
]
for x in list(dict.fromkeys(headlines)):
if x.text.strip() not in unwanted:
print(x.text.strip())
#Output : pip install bs4
[END]
|
Word guessing game in Python
|
https://www.geeksforgeeks.org/python-program-for-word-guessing-game/
|
import random
# library that we use in order to choose
# on random words from a list of words
name = input("What is your name? ")
# Here the user is asked to enter the name first
print("Good Luck ! ", name)
words = [
"rainbow",
"computer",
"science",
"programming",
"python",
"mathematics",
"player",
"condition",
"reverse",
"water",
"board",
"geeks",
]
# Function will choose one random
# word from this list of words
word = random.choice(words)
print("Guess the characters")
guesses = ""
# any number of turns can be used here
turns = 12
while turns > 0:
# counts the number of times a user fails
failed = 0
# all characters from the input
# word taking one at a time.
for char in word:
# comparing that character with
# the character in guesses
if char in guesses:
print(char, end=" ")
else:
print("_")
# for every failure 1 will be
# incremented in failure
failed += 1
if failed == 0:
# user will win the game if failure is 0
# and 'You Win' will be given as output
print("You Win")
# this print the correct word
print("The word is: ", word)
break
# if user has input the wrong alphabet then
# it will ask user to enter another alphabet
print()
guess = input("guess a character:")
# every input character will be stored in guesses
guesses += guess
# check input with the character in word
if guess not in word:
turns -= 1
# if the character doesn?????????t match the word
# then ?????????Wrong????????? will be given as out"Wrong")
# this will print the number of
# turns left for the user
print("You have", +turns, "more guesses")
if turns == 0:
print("You Loose")
|
#Output : What is your name? Gautam
|
Word guessing game in Python
import random
# library that we use in order to choose
# on random words from a list of words
name = input("What is your name? ")
# Here the user is asked to enter the name first
print("Good Luck ! ", name)
words = [
"rainbow",
"computer",
"science",
"programming",
"python",
"mathematics",
"player",
"condition",
"reverse",
"water",
"board",
"geeks",
]
# Function will choose one random
# word from this list of words
word = random.choice(words)
print("Guess the characters")
guesses = ""
# any number of turns can be used here
turns = 12
while turns > 0:
# counts the number of times a user fails
failed = 0
# all characters from the input
# word taking one at a time.
for char in word:
# comparing that character with
# the character in guesses
if char in guesses:
print(char, end=" ")
else:
print("_")
# for every failure 1 will be
# incremented in failure
failed += 1
if failed == 0:
# user will win the game if failure is 0
# and 'You Win' will be given as output
print("You Win")
# this print the correct word
print("The word is: ", word)
break
# if user has input the wrong alphabet then
# it will ask user to enter another alphabet
print()
guess = input("guess a character:")
# every input character will be stored in guesses
guesses += guess
# check input with the character in word
if guess not in word:
turns -= 1
# if the character doesn?????????t match the word
# then ?????????Wrong????????? will be given as out"Wrong")
# this will print the number of
# turns left for the user
print("You have", +turns, "more guesses")
if turns == 0:
print("You Loose")
#Output : What is your name? Gautam
[END]
|
Word guessing game in Python
|
https://www.geeksforgeeks.org/python-program-for-word-guessing-game/
|
import random
def isword(user_word,wordly_word):
for x in user_word:
print(x,end=" ")
print()
#If alphabet present in same position green
#if alphabet present in word yellow
#if alphabet is not present black
for i in range(len(user_word)):
if user_word[i] == wordly_word[i]:
print("????",end ="")
elif user_word[i] in wordly_word:
print("????",end="")
else:
print("",end="")
#if word present return true else return false
if user_word == wordly_word:
return 1
else:
return 0
import random
random_word = random.choice(words)
print(random_word)
print("Let's Play Wordle")
message,i = {0:"Marvellous",1:"Excellent",2:"Very good",3:"Nice",4:"Good",5:"Ok"},6
while i>0:
user_word=input("\nEnter word: ")
if (len(user_word)==5 and user_word.isalpha()):
i = i-1
if isword(user_word,random_word):
print("\n",message[i])
break
else:
continue
else:
print("Please enter a valid word")
else:
print("End of Game, the correct word is:",random_word)
|
From code
|
Word guessing game in Python
import random
def isword(user_word,wordly_word):
for x in user_word:
print(x,end=" ")
print()
#If alphabet present in same position green
#if alphabet present in word yellow
#if alphabet is not present black
for i in range(len(user_word)):
if user_word[i] == wordly_word[i]:
print("????",end ="")
elif user_word[i] in wordly_word:
print("????",end="")
else:
print("",end="")
#if word present return true else return false
if user_word == wordly_word:
return 1
else:
return 0
import random
random_word = random.choice(words)
print(random_word)
print("Let's Play Wordle")
message,i = {0:"Marvellous",1:"Excellent",2:"Very good",3:"Nice",4:"Good",5:"Ok"},6
while i>0:
user_word=input("\nEnter word: ")
if (len(user_word)==5 and user_word.isalpha()):
i = i-1
if isword(user_word,random_word):
print("\n",message[i])
break
else:
continue
else:
print("Please enter a valid word")
else:
print("End of Game, the correct word is:",random_word)
From code
[END]
|
Hangman Game in Python
|
https://www.geeksforgeeks.org/hangman-game-python/
|
# Python Program to illustrate# Hangman Gameimport randomfrom collections import Counter??????someWords = '''apple banana mango strawberryorange grape pineapple apricot lemon coconut watermeloncherry papaya berry peach lychee muskmelon'''??????someWords = someWords.split(' ')# randomly choose a secret word f"someWords" LIST.word = random.choice(someWords)??????if __name__ == '__main__':????????????????????????print('Guess the word! HINT: word is a name of a fruit')??????????????????????????????for i in word:??????????????????????????????????????????????????????# For printing the empty spaces for letters of the word????????????????????????????????????????????????print('_', end=' ')????????????????????????print()??????????????????????????????playing = True????????????????????????# list for storing the letters guessed by the player????????????????????????letterGuessed = ''????????????????????????chances = len(word) + 2????????????????????????correct = 0????????????????????????flag = 0????????????????????????try:????????????????????????????????????????????????while (chances != 0) and flag == 0:?????? # flag is updated when the word is correctly guessed????????????????????????????????????????????????????????????????????????print()????????????????????????????????????????????????????????????????????????chances -= 1???????????????y a LETTER')????????????????????????????????????????????????????????????????????????????????????????????????continue????????????????????????????????????????????????????????????????????????else if len(guess) & gt????????????????????????????????????????????????????????????????????????1:????????????????????????????????????????????????????????????????????????????????????????????????print('Enter only a SINGLE letter')????????????????????????????????????????????????????????????????????????????????????????????????continue????????????????????????????????????????????????????????????????????????else if guess in letterGuessed:????????????????????????????????????????????????????????????????????????????????????????????????print('You have already guessed that letter')????????????????????????????????????????????????????????????????????????????????????????????????continue??????????????????????????????????????????????????????????????????????????????# If letter is guessed correctly?????????????????????????????????????????????????????????????????????????print(char, end=' ')????????????????????????????????????????correct += 1????????????????????????????????# If user has guessed all the letters????????????????????????????????# Once the correct word is guessed fully,????????????????????????????????else if (Counter(letterGuessed) == Counter(word)):????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????# the game ends, even if chances remain????????????????????????????????????????print(& quot??????????????????????????????????????????????????????The word is: & quot??????????????????????????????????????????????????????, end=' ')????????????????????????????????????????print(word)????????????????????????????????????????flag = 1????????????????????????????????????????print('Congratulations, You won!')????????????????????????????????????????break?? # To break out of the for loop????????????????????????????????????????break?? # To break out of the while loop????????????????????????????????else:????????????????????????????????????????print('_', end=' ')??????????????????# If user has used all of his chances????????????????if chances & lt????????????????= 0 and (Counter(letterGuessed) != Counter(word)):????????????????????????print()????????????????????????print('You lost! Try again..')????????????????????????print('The word was {}'.format(word))??????????except KeyboardInterrupt:????????????????print()????????????????print('Bye! Try again.')????????????????exit()
|
#Output : omkarpathak@omkarpathak-Inspiron-3542:~/Documents/
|
Hangman Game in Python
# Python Program to illustrate# Hangman Gameimport randomfrom collections import Counter??????someWords = '''apple banana mango strawberryorange grape pineapple apricot lemon coconut watermeloncherry papaya berry peach lychee muskmelon'''??????someWords = someWords.split(' ')# randomly choose a secret word f"someWords" LIST.word = random.choice(someWords)??????if __name__ == '__main__':????????????????????????print('Guess the word! HINT: word is a name of a fruit')??????????????????????????????for i in word:??????????????????????????????????????????????????????# For printing the empty spaces for letters of the word????????????????????????????????????????????????print('_', end=' ')????????????????????????print()??????????????????????????????playing = True????????????????????????# list for storing the letters guessed by the player????????????????????????letterGuessed = ''????????????????????????chances = len(word) + 2????????????????????????correct = 0????????????????????????flag = 0????????????????????????try:????????????????????????????????????????????????while (chances != 0) and flag == 0:?????? # flag is updated when the word is correctly guessed????????????????????????????????????????????????????????????????????????print()????????????????????????????????????????????????????????????????????????chances -= 1???????????????y a LETTER')????????????????????????????????????????????????????????????????????????????????????????????????continue????????????????????????????????????????????????????????????????????????else if len(guess) & gt????????????????????????????????????????????????????????????????????????1:????????????????????????????????????????????????????????????????????????????????????????????????print('Enter only a SINGLE letter')????????????????????????????????????????????????????????????????????????????????????????????????continue????????????????????????????????????????????????????????????????????????else if guess in letterGuessed:????????????????????????????????????????????????????????????????????????????????????????????????print('You have already guessed that letter')????????????????????????????????????????????????????????????????????????????????????????????????continue??????????????????????????????????????????????????????????????????????????????# If letter is guessed correctly?????????????????????????????????????????????????????????????????????????print(char, end=' ')????????????????????????????????????????correct += 1????????????????????????????????# If user has guessed all the letters????????????????????????????????# Once the correct word is guessed fully,????????????????????????????????else if (Counter(letterGuessed) == Counter(word)):????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????# the game ends, even if chances remain????????????????????????????????????????print(& quot??????????????????????????????????????????????????????The word is: & quot??????????????????????????????????????????????????????, end=' ')????????????????????????????????????????print(word)????????????????????????????????????????flag = 1????????????????????????????????????????print('Congratulations, You won!')????????????????????????????????????????break?? # To break out of the for loop????????????????????????????????????????break?? # To break out of the while loop????????????????????????????????else:????????????????????????????????????????print('_', end=' ')??????????????????# If user has used all of his chances????????????????if chances & lt????????????????= 0 and (Counter(letterGuessed) != Counter(word)):????????????????????????print()????????????????????????print('You lost! Try again..')????????????????????????print('The word was {}'.format(word))??????????except KeyboardInterrupt:????????????????print()????????????????print('Bye! Try again.')????????????????exit()
#Output : omkarpathak@omkarpathak-Inspiron-3542:~/Documents/
[END]
|
21 Number game in Python
|
https://www.geeksforgeeks.org/21-number-game-in-python/
|
# Python code to play 21 Number game
# returns the nearest multiple to 4
def nearestMultiple(num):
if num >= 4:
near = num + (4 - (num % 4))
else:
near = 4
return near
def lose1():
print("\n\nYOU LOSE !")
print("Better luck next time !")
exit(0)
# checks whether the numbers are consecutive
def check(xyz):
i = 1
while i < len(xyz):
if (xyz[i] - xyz[i - 1]) != 1:
return False
i = i + 1
return True
# starts the game
def start1():
xyz = []
last = 0
while True:
print("Enter 'F' to take the first chance.")
print("Enter 'S' to take the second chance.")
chance = input("> ")
# player takes the first chance
if chance == "F":
while True:
if last == 20:
lose1()
else:
print("\nYour Turn.")
print("\nHow many numbers do you wish to enter?")
inp = int(input("> "))
if inp > 0 and inp <= 3:
comp = 4 - inp
else:
print("Wrong input. You are disqualified from the game.")
lose1()
i, j = 1, 1
print("Now enter the values")
while i <= inp:
a = input("> ")
a = int(a)
xyz.append(a)
i = i + 1
# store the last element of xyz.
last = xyz[-1]
# checks whether the input
# numbers are consecutive
if check(xyz) == True:
if last == 21:
lose1()
else:
# "Computer's turn."
while j <= comp:
xyz.append(last + j)
j = j + 1
print("Order of inputs after computer's turn is: ")
print(xyz)
last = xyz[-1]
else:
print("\nYou did not input consecutive integers.")
lose1()
# player takes the second chance
elif chance == "S":
comp = 1
last = 0
while last < 20:
# "Computer's turn"
j = 1
while j <= comp:
xyz.append(last + j)
j = j + 1
print("Order of inputs after computer's turn is:")
print(xyz)
if xyz[-1] == 20:
lose1()
else:
print("\nYour turn.")
print("\nHow many numbers do you wish to enter?")
inp = input("> ")
inp = int(inp)
i = 1
print("Enter your values")
while i <= inp:
xyz.append(int(input("> ")))
i = i + 1
last = xyz[-1]
if check(xyz) == True:
# print (xyz)
near = nearestMultiple(last)
comp = near - last
if comp == 4:
comp = 3
else:
comp = comp
else:
# if inputs are not consecutive
# automatically disqualified
print("\nYou did not input consecutive integers.")
# print ("You are disqualified from the game.")
lose1()
print("\n\nCONGRATULATIONS !!!")
print("YOU WON !")
exit(0)
else:
print("wrong choice")
game = True
while game == True:
print("Player 2 is Computer.")
print("Do you want to play the 21 number game? (Yes / No)")
ans = input("> ")
if ans == "Yes":
start1()
else:
print("Do you want quit the game?(yes / no)")
nex = input("> ")
if nex == "yes":
print("You are quitting the game...")
exit(0)
elif nex == "no":
print("Continuing...")
else:
print("Wrong choice")
|
#Output : Player 2 is Computer.
|
21 Number game in Python
# Python code to play 21 Number game
# returns the nearest multiple to 4
def nearestMultiple(num):
if num >= 4:
near = num + (4 - (num % 4))
else:
near = 4
return near
def lose1():
print("\n\nYOU LOSE !")
print("Better luck next time !")
exit(0)
# checks whether the numbers are consecutive
def check(xyz):
i = 1
while i < len(xyz):
if (xyz[i] - xyz[i - 1]) != 1:
return False
i = i + 1
return True
# starts the game
def start1():
xyz = []
last = 0
while True:
print("Enter 'F' to take the first chance.")
print("Enter 'S' to take the second chance.")
chance = input("> ")
# player takes the first chance
if chance == "F":
while True:
if last == 20:
lose1()
else:
print("\nYour Turn.")
print("\nHow many numbers do you wish to enter?")
inp = int(input("> "))
if inp > 0 and inp <= 3:
comp = 4 - inp
else:
print("Wrong input. You are disqualified from the game.")
lose1()
i, j = 1, 1
print("Now enter the values")
while i <= inp:
a = input("> ")
a = int(a)
xyz.append(a)
i = i + 1
# store the last element of xyz.
last = xyz[-1]
# checks whether the input
# numbers are consecutive
if check(xyz) == True:
if last == 21:
lose1()
else:
# "Computer's turn."
while j <= comp:
xyz.append(last + j)
j = j + 1
print("Order of inputs after computer's turn is: ")
print(xyz)
last = xyz[-1]
else:
print("\nYou did not input consecutive integers.")
lose1()
# player takes the second chance
elif chance == "S":
comp = 1
last = 0
while last < 20:
# "Computer's turn"
j = 1
while j <= comp:
xyz.append(last + j)
j = j + 1
print("Order of inputs after computer's turn is:")
print(xyz)
if xyz[-1] == 20:
lose1()
else:
print("\nYour turn.")
print("\nHow many numbers do you wish to enter?")
inp = input("> ")
inp = int(inp)
i = 1
print("Enter your values")
while i <= inp:
xyz.append(int(input("> ")))
i = i + 1
last = xyz[-1]
if check(xyz) == True:
# print (xyz)
near = nearestMultiple(last)
comp = near - last
if comp == 4:
comp = 3
else:
comp = comp
else:
# if inputs are not consecutive
# automatically disqualified
print("\nYou did not input consecutive integers.")
# print ("You are disqualified from the game.")
lose1()
print("\n\nCONGRATULATIONS !!!")
print("YOU WON !")
exit(0)
else:
print("wrong choice")
game = True
while game == True:
print("Player 2 is Computer.")
print("Do you want to play the 21 number game? (Yes / No)")
ans = input("> ")
if ans == "Yes":
start1()
else:
print("Do you want quit the game?(yes / no)")
nex = input("> ")
if nex == "yes":
print("You are quitting the game...")
exit(0)
elif nex == "no":
print("Continuing...")
else:
print("Wrong choice")
#Output : Player 2 is Computer.
[END]
|
Mastermind Game using Python
|
https://www.geeksforgeeks.org/mastermind-game-using-python/
|
import random????????????# the .randrange() function generates a# random number within the specified range.num = random.randrange(1000, 10000)??????n "Guess the 4 digit number:"))??????# condition to test equality of the# guess made. Program terminates if true.if (n == num):??????????"Great! You guessed the number in just 1 try! You're a Mastermind!")else:????????????????????????# ctr variable initialized. It will keep count of????????????????????????# the number of tries the Player takes to guess the number.????????????????????????ctr = 0??????????????????????????????# while loop repeats as long as the????????????????????????# Player fails to guess the number correctly.????????????????????????while (n != num):????????????????????????????????????????????????# variable increments every time the loop????????????????????????????????????????????????# is executed, giving an idea of how many????????????????????????????????????????????????# guesses were made.????????????????????????????????????????????????ctr += 1??????????????????????????????????????????????????????count = 0??????????????????????????????????????????????????????# explicit type conversion of an integer to????????????????????????????????????????????????# a string in order to ease extraction of digits????????????????????????????????????????????????n = str(n)????????????????????????????????????????um[i]):????????????????????????????????????????????????????????????????????????????????????????????????# number of digits guessed correctly increments????????????????????????????????????????????????????????????????????????????????????????????????count += 1????????????????????????????????????????????????????????????????????????????????????????????????# hence, the digit is stored in correct[].????????????????????????????????????????????????????????????????????????????????????????????????correct[i] = n[i]?????????????????????????????????????????????????"Not quite the number. But you did get ",???????????????????????????????????????????" digit(s) correct!")????????????????????????????????????????????????????????????# second code is not supposed to print the guessed numbers, from the sample output, here I get we are not recording the position of the guess,but count. But as per the explanation, the code should not print the guessed numbers, rather give thei"Also these numbers in your input were correct.")????????????????????????????????????????????????????????????????????????# for k in correct:????????????????????????????????????????????????????????????????????????#?????????????????? print"Enter your next choice of numbers: "))??????????????????????????????????????????????????????# when none of the digits are guessed correctly.????????????????????????????"None of the numbers in your input match.")??????????????????????????????????????"Enter your next choice of numbers: "))??????????????????????????????# condition for equality.????????????????????????if n == num:????????????????????????# ctr must be incremented when the n==num gets executed as we have the other incrmentation in the n!=num condi"You've become a Mastermind!")??????????????????????"It took you only", ctr, "tries.")
|
#Output : Player 1, set the number: 5672
|
Mastermind Game using Python
import random????????????# the .randrange() function generates a# random number within the specified range.num = random.randrange(1000, 10000)??????n "Guess the 4 digit number:"))??????# condition to test equality of the# guess made. Program terminates if true.if (n == num):??????????"Great! You guessed the number in just 1 try! You're a Mastermind!")else:????????????????????????# ctr variable initialized. It will keep count of????????????????????????# the number of tries the Player takes to guess the number.????????????????????????ctr = 0??????????????????????????????# while loop repeats as long as the????????????????????????# Player fails to guess the number correctly.????????????????????????while (n != num):????????????????????????????????????????????????# variable increments every time the loop????????????????????????????????????????????????# is executed, giving an idea of how many????????????????????????????????????????????????# guesses were made.????????????????????????????????????????????????ctr += 1??????????????????????????????????????????????????????count = 0??????????????????????????????????????????????????????# explicit type conversion of an integer to????????????????????????????????????????????????# a string in order to ease extraction of digits????????????????????????????????????????????????n = str(n)????????????????????????????????????????um[i]):????????????????????????????????????????????????????????????????????????????????????????????????# number of digits guessed correctly increments????????????????????????????????????????????????????????????????????????????????????????????????count += 1????????????????????????????????????????????????????????????????????????????????????????????????# hence, the digit is stored in correct[].????????????????????????????????????????????????????????????????????????????????????????????????correct[i] = n[i]?????????????????????????????????????????????????"Not quite the number. But you did get ",???????????????????????????????????????????" digit(s) correct!")????????????????????????????????????????????????????????????# second code is not supposed to print the guessed numbers, from the sample output, here I get we are not recording the position of the guess,but count. But as per the explanation, the code should not print the guessed numbers, rather give thei"Also these numbers in your input were correct.")????????????????????????????????????????????????????????????????????????# for k in correct:????????????????????????????????????????????????????????????????????????#?????????????????? print"Enter your next choice of numbers: "))??????????????????????????????????????????????????????# when none of the digits are guessed correctly.????????????????????????????"None of the numbers in your input match.")??????????????????????????????????????"Enter your next choice of numbers: "))??????????????????????????????# condition for equality.????????????????????????if n == num:????????????????????????# ctr must be incremented when the n==num gets executed as we have the other incrmentation in the n!=num condi"You've become a Mastermind!")??????????????????????"It took you only", ctr, "tries.")
#Output : Player 1, set the number: 5672
[END]
|
Mastermind Game using Python
|
https://www.geeksforgeeks.org/mastermind-game-using-python/
|
import random
# the .randrange() function generates
# a random number within the specified range.
num = random.randrange(1000, 10000)
n = int(input("Guess the 4 digit number:"))
# condition to test equality of the
# guess made. Program terminates if true.
if n == num:
print("Great! You guessed the number in just 1 try! You're a Mastermind!")
else:
# ctr variable initialized. It will keep count of
# the number of tries the Player takes to guess the number.
ctr = 0
# while loop repeats as long as the Player
# fails to guess the number correctly.
while n != num:
# variable increments every time the loop
# is executed, giving an idea of how many
# guesses were made.
ctr += 1
count = 0
# explicit type conversion of an integer to
# a string in order to ease extraction of digits
n = str(n)
# explicit type conversion of a string to an integer
num = str(num)
# correct[] list stores digits which are correct
correct = []
# for loop runs 4 times since the number has 4 digits.
for i in range(0, 4):
# checking for equality of digits
if n[i] == num[i]:
# number of digits guessed correctly increments
count += 1
# hence, the digit is stored in correct[].
correct.append(n[i])
else:
continue
# when not all the digits are guessed correctly.
if (count < 4) and (count != 0):
print("Not quite the number. But you did get ", count, " digit(s) correct!")
print("Also these numbers in your input were correct.")
for k in correct:
print(k, end=" ")
print("\n")
print("\n")
n = int(input("Enter your next choice of numbers: "))
# when none of the digits are guessed correctly.
elif count == 0:
print("None of the numbers in your input match.")
n = int(input("Enter your next choice of numbers: "))
if n == num:
print("You've become a Mastermind!")
print("It took you only", ctr, "tries.")
|
#Output : Player 1, set the number: 5672
|
Mastermind Game using Python
import random
# the .randrange() function generates
# a random number within the specified range.
num = random.randrange(1000, 10000)
n = int(input("Guess the 4 digit number:"))
# condition to test equality of the
# guess made. Program terminates if true.
if n == num:
print("Great! You guessed the number in just 1 try! You're a Mastermind!")
else:
# ctr variable initialized. It will keep count of
# the number of tries the Player takes to guess the number.
ctr = 0
# while loop repeats as long as the Player
# fails to guess the number correctly.
while n != num:
# variable increments every time the loop
# is executed, giving an idea of how many
# guesses were made.
ctr += 1
count = 0
# explicit type conversion of an integer to
# a string in order to ease extraction of digits
n = str(n)
# explicit type conversion of a string to an integer
num = str(num)
# correct[] list stores digits which are correct
correct = []
# for loop runs 4 times since the number has 4 digits.
for i in range(0, 4):
# checking for equality of digits
if n[i] == num[i]:
# number of digits guessed correctly increments
count += 1
# hence, the digit is stored in correct[].
correct.append(n[i])
else:
continue
# when not all the digits are guessed correctly.
if (count < 4) and (count != 0):
print("Not quite the number. But you did get ", count, " digit(s) correct!")
print("Also these numbers in your input were correct.")
for k in correct:
print(k, end=" ")
print("\n")
print("\n")
n = int(input("Enter your next choice of numbers: "))
# when none of the digits are guessed correctly.
elif count == 0:
print("None of the numbers in your input match.")
n = int(input("Enter your next choice of numbers: "))
if n == num:
print("You've become a Mastermind!")
print("It took you only", ctr, "tries.")
#Output : Player 1, set the number: 5672
[END]
|
2048 Game in Python
|
https://www.geeksforgeeks.org/2048-game-in-python/
|
# logic.py to be
# imported in the 2048.py file
# importing random package
# for methods to generate random
# numbers.
import random
# function to initialize game / grid
# at the start
def start_game():
# declaring an empty list then
# appending 4 list each with four
# elements as 0.
mat = []
for i in range(4):
mat.append([0] * 4)
# printing controls for user
print("Commands are as follows : ")
print("'W' or 'w' : Move Up")
print("'S' or 's' : Move Down")
print("'A' or 'a' : Move Left")
print("'D' or 'd' : Move Right")
# calling the function to add
# a new 2 in grid after every step
add_new_2(mat)
return mat
# function to add a new 2 in
# grid at any random empty cell
def add_new_2(mat):
# choosing a random index for
# row and column.
r = random.randint(0, 3)
c = random.randint(0, 3)
# while loop will break as the
# random cell chosen will be empty
# (or contains zero)
while mat[r] != 0:
r = random.randint(0, 3)
c = random.randint(0, 3)
# we will place a 2 at that empty
# random cell.
mat[r] = 2
# function to get the current
# state of game
def get_current_state(mat):
# if any cell contains
# 2048 we have won
for i in range(4):
for j in range(4):
if mat[i][j] == 2048:
return "WON"
# if we are still left with
# atleast one empty cell
# game is not yet over
for i in range(4):
for j in range(4):
if mat[i][j] == 0:
return "GAME NOT OVER"
# or if no cell is empty now
# but if after any move left, right,
# up or down, if any two cells
# gets merged and create an empty
# cell then also game is not yet over
for i in range(3):
for j in range(3):
if mat[i][j] == mat[i + 1][j] or mat[i][j] == mat[i][j + 1]:
return "GAME NOT OVER"
for j in range(3):
if mat[3][j] == mat[3][j + 1]:
return "GAME NOT OVER"
for i in range(3):
if mat[i][3] == mat[i + 1][3]:
return "GAME NOT OVER"
# else we have lost the game
return "LOST"
# all the functions defined below
# are for left swap initially.
# function to compress the grid
# after every step before and
# after merging cells.
def compress(mat):
# bool variable to determine
# any change happened or not
changed = False
# empty grid
new_mat = []
# with all cells empty
for i in range(4):
new_mat.append([0] * 4)
# here we will shift entries
# of each cell to it's extreme
# left row by row
# loop to traverse rows
for i in range(4):
pos = 0
# loop to traverse each column
# in respective row
for j in range(4):
if mat[i][j] != 0:
# if cell is non empty then
# we will shift it's number to
# previous empty cell in that row
# denoted by pos variable
new_mat[i][pos] = mat[i][j]
if j != pos:
changed = True
pos += 1
# returning new compressed matrix
# and the flag variable.
return new_mat, changed
# function to merge the cells
# in matrix after compressing
def merge(mat):
changed = False
for i in range(4):
for j in range(3):
# if current cell has same value as
# next cell in the row and they
# are non empty then
if mat[i][j] == mat[i][j + 1] and mat[i][j] != 0:
# double current cell value and
# empty the next cell
mat[i][j] = mat[i][j] * 2
mat[i][j + 1] = 0
# make bool variable True indicating
# the new grid after merging is
# different.
changed = True
return mat, changed
# function to reverse the matrix
# means reversing the content of
# each row (reversing the sequence)
def reverse(mat):
new_mat = []
for i in range(4):
new_mat.append([])
for j in range(4):
new_mat[i].append(mat[i][3 - j])
return new_mat
# function to get the transpose
# of matrix means interchanging
# rows and column
def transpose(mat):
new_mat = []
for i in range(4):
new_mat.append([])
for j in range(4):
new_mat[i].append(mat[j][i])
return new_mat
# function to update the matrix
# if we move / swipe left
def move_left(grid):
# first compress the grid
new_grid, changed1 = compress(grid)
# then merge the cells.
new_grid, changed2 = merge(new_grid)
changed = changed1 or changed2
# again compress after merging.
new_grid, temp = compress(new_grid)
# return new matrix and bool changed
# telling whether the grid is same
# or different
return new_grid, changed
# function to update the matrix
# if we move / swipe right
def move_right(grid):
# to move right we just reverse
# the matrix
new_grid = reverse(grid)
# then move left
new_grid, changed = move_left(new_grid)
# then again reverse matrix will
# give us desired result
new_grid = reverse(new_grid)
return new_grid, changed
# function to update the matrix
# if we move / swipe up
def move_up(grid):
# to move up we just take
# transpose of matrix
new_grid = transpose(grid)
# then move left (calling all
# included functions) then
new_grid, changed = move_left(new_grid)
# again take transpose will give
# desired results
new_grid = transpose(new_grid)
return new_grid, changed
# function to update the matrix
# if we move / swipe down
def move_down(grid):
# to move down we take transpose
new_grid = transpose(grid)
# move right and then again
new_grid, changed = move_right(new_grid)
# take transpose will give desired
# results.
new_grid = transpose(new_grid)
return new_grid, changed
# this file only contains all the logic
# functions to be called in main function
# present in the other file
|
#Output : Commands are as follows :
|
2048 Game in Python
# logic.py to be
# imported in the 2048.py file
# importing random package
# for methods to generate random
# numbers.
import random
# function to initialize game / grid
# at the start
def start_game():
# declaring an empty list then
# appending 4 list each with four
# elements as 0.
mat = []
for i in range(4):
mat.append([0] * 4)
# printing controls for user
print("Commands are as follows : ")
print("'W' or 'w' : Move Up")
print("'S' or 's' : Move Down")
print("'A' or 'a' : Move Left")
print("'D' or 'd' : Move Right")
# calling the function to add
# a new 2 in grid after every step
add_new_2(mat)
return mat
# function to add a new 2 in
# grid at any random empty cell
def add_new_2(mat):
# choosing a random index for
# row and column.
r = random.randint(0, 3)
c = random.randint(0, 3)
# while loop will break as the
# random cell chosen will be empty
# (or contains zero)
while mat[r] != 0:
r = random.randint(0, 3)
c = random.randint(0, 3)
# we will place a 2 at that empty
# random cell.
mat[r] = 2
# function to get the current
# state of game
def get_current_state(mat):
# if any cell contains
# 2048 we have won
for i in range(4):
for j in range(4):
if mat[i][j] == 2048:
return "WON"
# if we are still left with
# atleast one empty cell
# game is not yet over
for i in range(4):
for j in range(4):
if mat[i][j] == 0:
return "GAME NOT OVER"
# or if no cell is empty now
# but if after any move left, right,
# up or down, if any two cells
# gets merged and create an empty
# cell then also game is not yet over
for i in range(3):
for j in range(3):
if mat[i][j] == mat[i + 1][j] or mat[i][j] == mat[i][j + 1]:
return "GAME NOT OVER"
for j in range(3):
if mat[3][j] == mat[3][j + 1]:
return "GAME NOT OVER"
for i in range(3):
if mat[i][3] == mat[i + 1][3]:
return "GAME NOT OVER"
# else we have lost the game
return "LOST"
# all the functions defined below
# are for left swap initially.
# function to compress the grid
# after every step before and
# after merging cells.
def compress(mat):
# bool variable to determine
# any change happened or not
changed = False
# empty grid
new_mat = []
# with all cells empty
for i in range(4):
new_mat.append([0] * 4)
# here we will shift entries
# of each cell to it's extreme
# left row by row
# loop to traverse rows
for i in range(4):
pos = 0
# loop to traverse each column
# in respective row
for j in range(4):
if mat[i][j] != 0:
# if cell is non empty then
# we will shift it's number to
# previous empty cell in that row
# denoted by pos variable
new_mat[i][pos] = mat[i][j]
if j != pos:
changed = True
pos += 1
# returning new compressed matrix
# and the flag variable.
return new_mat, changed
# function to merge the cells
# in matrix after compressing
def merge(mat):
changed = False
for i in range(4):
for j in range(3):
# if current cell has same value as
# next cell in the row and they
# are non empty then
if mat[i][j] == mat[i][j + 1] and mat[i][j] != 0:
# double current cell value and
# empty the next cell
mat[i][j] = mat[i][j] * 2
mat[i][j + 1] = 0
# make bool variable True indicating
# the new grid after merging is
# different.
changed = True
return mat, changed
# function to reverse the matrix
# means reversing the content of
# each row (reversing the sequence)
def reverse(mat):
new_mat = []
for i in range(4):
new_mat.append([])
for j in range(4):
new_mat[i].append(mat[i][3 - j])
return new_mat
# function to get the transpose
# of matrix means interchanging
# rows and column
def transpose(mat):
new_mat = []
for i in range(4):
new_mat.append([])
for j in range(4):
new_mat[i].append(mat[j][i])
return new_mat
# function to update the matrix
# if we move / swipe left
def move_left(grid):
# first compress the grid
new_grid, changed1 = compress(grid)
# then merge the cells.
new_grid, changed2 = merge(new_grid)
changed = changed1 or changed2
# again compress after merging.
new_grid, temp = compress(new_grid)
# return new matrix and bool changed
# telling whether the grid is same
# or different
return new_grid, changed
# function to update the matrix
# if we move / swipe right
def move_right(grid):
# to move right we just reverse
# the matrix
new_grid = reverse(grid)
# then move left
new_grid, changed = move_left(new_grid)
# then again reverse matrix will
# give us desired result
new_grid = reverse(new_grid)
return new_grid, changed
# function to update the matrix
# if we move / swipe up
def move_up(grid):
# to move up we just take
# transpose of matrix
new_grid = transpose(grid)
# then move left (calling all
# included functions) then
new_grid, changed = move_left(new_grid)
# again take transpose will give
# desired results
new_grid = transpose(new_grid)
return new_grid, changed
# function to update the matrix
# if we move / swipe down
def move_down(grid):
# to move down we take transpose
new_grid = transpose(grid)
# move right and then again
new_grid, changed = move_right(new_grid)
# take transpose will give desired
# results.
new_grid = transpose(new_grid)
return new_grid, changed
# this file only contains all the logic
# functions to be called in main function
# present in the other file
#Output : Commands are as follows :
[END]
|
2048 Game in Python
|
https://www.geeksforgeeks.org/2048-game-in-python/
|
# 2048.py
# importing the logic.py file
# where we have written all the
# logic functions used.
import logic
# Driver code
if __name__ == "__main__":
# calling start_game function
# to initialize the matrix
mat = logic.start_game()
while True:
# taking the user input
# for next step
x = input("Press the command : ")
# we have to move up
if x == "W" or x == "w":
# call the move_up function
mat, flag = logic.move_up(mat)
# get the current state and print it
status = logic.get_current_state(mat)
print(status)
# if game not over then continue
# and add a new two
if status == "GAME NOT OVER":
logic.add_new_2(mat)
# else break the loop
else:
break
# the above process will be followed
# in case of each type of move
# below
# to move down
elif x == "S" or x == "s":
mat, flag = logic.move_down(mat)
status = logic.get_current_state(mat)
print(status)
if status == "GAME NOT OVER":
logic.add_new_2(mat)
else:
break
# to move left
elif x == "A" or x == "a":
mat, flag = logic.move_left(mat)
status = logic.get_current_state(mat)
print(status)
if status == "GAME NOT OVER":
logic.add_new_2(mat)
else:
break
# to move right
elif x == "D" or x == "d":
mat, flag = logic.move_right(mat)
status = logic.get_current_state(mat)
print(status)
if status == "GAME NOT OVER":
logic.add_new_2(mat)
else:
break
else:
print("Invalid Key Pressed")
# print the matrix after each
# move.
print(mat)
|
#Output : Commands are as follows :
|
2048 Game in Python
# 2048.py
# importing the logic.py file
# where we have written all the
# logic functions used.
import logic
# Driver code
if __name__ == "__main__":
# calling start_game function
# to initialize the matrix
mat = logic.start_game()
while True:
# taking the user input
# for next step
x = input("Press the command : ")
# we have to move up
if x == "W" or x == "w":
# call the move_up function
mat, flag = logic.move_up(mat)
# get the current state and print it
status = logic.get_current_state(mat)
print(status)
# if game not over then continue
# and add a new two
if status == "GAME NOT OVER":
logic.add_new_2(mat)
# else break the loop
else:
break
# the above process will be followed
# in case of each type of move
# below
# to move down
elif x == "S" or x == "s":
mat, flag = logic.move_down(mat)
status = logic.get_current_state(mat)
print(status)
if status == "GAME NOT OVER":
logic.add_new_2(mat)
else:
break
# to move left
elif x == "A" or x == "a":
mat, flag = logic.move_left(mat)
status = logic.get_current_state(mat)
print(status)
if status == "GAME NOT OVER":
logic.add_new_2(mat)
else:
break
# to move right
elif x == "D" or x == "d":
mat, flag = logic.move_right(mat)
status = logic.get_current_state(mat)
print(status)
if status == "GAME NOT OVER":
logic.add_new_2(mat)
else:
break
else:
print("Invalid Key Pressed")
# print the matrix after each
# move.
print(mat)
#Output : Commands are as follows :
[END]
|
Flames game in Python
|
https://www.geeksforgeeks.org/python-program-to-implement-simple-flames-game/
|
# function for removing common characters
# with their respective occurrences
def remove_match_char(list1, list2):
for i in range(len(list1)):
for j in range(len(list2)):
# if common character is found
# then remove that character
# and return list of concatenated
# list with True Flag
if list1[i] == list2[j]:
c = list1[i]
# remove character from the list
list1.remove(c)
list2.remove(c)
# concatenation of two list elements with *
# * is act as border mark here
list3 = list1 + ["*"] + list2
# return the concatenated list with True flag
return [list3, True]
# no common characters is found
# return the concatenated list with False flag
list3 = list1 + ["*"] + list2
return [list3, False]
# Driver code
if __name__ == "__main__":
# take first name
p1 = input("Player 1 name : ")
# converted all letters into lower case
p1 = p1.lower()
# replace any space with empty string
p1.replace(" ", "")
# make a list of letters or characters
p1_list = list(p1)
# take 2nd name
p2 = input("Player 2 name : ")
p2 = p2.lower()
p2.replace(" ", "")
p2_list = list(p2)
# taking a flag as True initially
proceed = True
# keep calling remove_match_char function
# until common characters is found or
# keep looping until proceed flag is True
while proceed:
# function calling and store return value
ret_list = remove_match_char(p1_list, p2_list)
# take out concatenated list from return list
con_list = ret_list[0]
# take out flag value from return list
proceed = ret_list[1]
# find the index of "*" / border mark
star_index = con_list.index("*")
# list slicing perform
# all characters before * store in p1_list
p1_list = con_list[:star_index]
# all characters after * store in p2_list
p2_list = con_list[star_index + 1 :]
# count total remaining characters
count = len(p1_list) + len(p2_list)
# list of FLAMES acronym
result = ["Friends", "Love", "Affection", "Marriage", "Enemy", "Siblings"]
# keep looping until only one item
# is not remaining in the result list
while len(result) > 1:
# store that index value from
# where we have to perform slicing.
split_index = count % len(result) - 1
# this steps is done for performing
# anticlock-wise circular fashion counting.
if split_index >= 0:
# list slicing
right = result[split_index + 1 :]
left = result[:split_index]
# list concatenation
result = right + left
else:
result = result[: len(result) - 1]
# print final result
print("Relationship status :", result[0])
|
#Input : player1 name : AJAY
player 2 name : PRIYA
|
Flames game in Python
# function for removing common characters
# with their respective occurrences
def remove_match_char(list1, list2):
for i in range(len(list1)):
for j in range(len(list2)):
# if common character is found
# then remove that character
# and return list of concatenated
# list with True Flag
if list1[i] == list2[j]:
c = list1[i]
# remove character from the list
list1.remove(c)
list2.remove(c)
# concatenation of two list elements with *
# * is act as border mark here
list3 = list1 + ["*"] + list2
# return the concatenated list with True flag
return [list3, True]
# no common characters is found
# return the concatenated list with False flag
list3 = list1 + ["*"] + list2
return [list3, False]
# Driver code
if __name__ == "__main__":
# take first name
p1 = input("Player 1 name : ")
# converted all letters into lower case
p1 = p1.lower()
# replace any space with empty string
p1.replace(" ", "")
# make a list of letters or characters
p1_list = list(p1)
# take 2nd name
p2 = input("Player 2 name : ")
p2 = p2.lower()
p2.replace(" ", "")
p2_list = list(p2)
# taking a flag as True initially
proceed = True
# keep calling remove_match_char function
# until common characters is found or
# keep looping until proceed flag is True
while proceed:
# function calling and store return value
ret_list = remove_match_char(p1_list, p2_list)
# take out concatenated list from return list
con_list = ret_list[0]
# take out flag value from return list
proceed = ret_list[1]
# find the index of "*" / border mark
star_index = con_list.index("*")
# list slicing perform
# all characters before * store in p1_list
p1_list = con_list[:star_index]
# all characters after * store in p2_list
p2_list = con_list[star_index + 1 :]
# count total remaining characters
count = len(p1_list) + len(p2_list)
# list of FLAMES acronym
result = ["Friends", "Love", "Affection", "Marriage", "Enemy", "Siblings"]
# keep looping until only one item
# is not remaining in the result list
while len(result) > 1:
# store that index value from
# where we have to perform slicing.
split_index = count % len(result) - 1
# this steps is done for performing
# anticlock-wise circular fashion counting.
if split_index >= 0:
# list slicing
right = result[split_index + 1 :]
left = result[:split_index]
# list concatenation
result = right + left
else:
result = result[: len(result) - 1]
# print final result
print("Relationship status :", result[0])
#Input : player1 name : AJAY
player 2 name : PRIYA
[END]
|
Pok??????mon Training
|
https://www.geeksforgeeks.org/python-pokemon-training-game/
|
# python code to train pokemon
powers = [3, 8, 9, 7]
mini, maxi = 0, 0
for power in powers:
if mini == 0 and maxi == 0:
mini, maxi = powers[0], powers[0]
print(mini, maxi)
else:
mini = min(mini, power)
maxi = max(maxi, power)
print(mini, maxi)
# Time Complexity is O(N) with Space Complexity O(1)
|
#Input :
|
Pok??????mon Training
# python code to train pokemon
powers = [3, 8, 9, 7]
mini, maxi = 0, 0
for power in powers:
if mini == 0 and maxi == 0:
mini, maxi = powers[0], powers[0]
print(mini, maxi)
else:
mini = min(mini, power)
maxi = max(maxi, power)
print(mini, maxi)
# Time Complexity is O(N) with Space Complexity O(1)
#Input :
[END]
|
Rock Paper Scissor game in Python
|
https://www.geeksforgeeks.org/python-program-implement-rock-paper-scissor-game/
|
# import random module
import random
# print multiline instruction
# performstring concatenation of string
print(
"Winning rules of the game ROCK PAPER SCISSORS are :\n"
+ "Rock vs Paper -> Paper wins \n"
+ "Rock vs Scissors -> Rock wins \n"
+ "Paper vs Scissors -> Scissor wins \n"
)
while True:
print("Enter your choice \n 1 - Rock \n 2 - Paper \n 3 - Scissors \n")
# take the input from user
choice = int(input("Enter your choice :"))
# OR is the short-circuit operator
# if any one of the condition is true
# then it return True value
# looping until user enter invalid input
while choice > 3 or choice < 1:
choice = int(input("Enter a valid choice please ???"))
# initialize value of choice_name variable
# corresponding to the choice value
if choice == 1:
choice_name = "Rock"
elif choice == 2:
choice_name = "Paper"
else:
choice_name = "Scissors"
# print user choice
print("User choice is \n", choice_name)
print("Now its Computers Turn....")
# Computer chooses randomly any number
# among 1 , 2 and 3. Using randint method
# of random module
comp_choice = random.randint(1, 3)
# looping until comp_choice value
# is equal to the choice value
while comp_choice == choice:
comp_choice = random.randint(1, 3)
# initialize value of comp_choice_name
# variable corresponding to the choice value
if comp_choice == 1:
comp_choice_name = "rocK"
elif comp_choice == 2:
comp_choice_name = "papeR"
else:
comp_choice_name = "scissoR"
print("Computer choice is \n", comp_choice_name)
print(choice_name, "Vs", comp_choice_name)
# we need to check of a draw
if choice == comp_choice:
print("Its a Draw", end="")
result = "DRAW"
# condition for winning
if choice == 1 and comp_choice == 2:
print("paper wins =>", end="")
result = "papeR"
elif choice == 2 and comp_choice == 1:
print("paper wins =>", end="")
result = "Paper"
if choice == 1 and comp_choice == 3:
print("Rock wins =>\n", end="")
result = "Rock"
elif choice == 3 and comp_choice == 1:
print("Rock wins =>\n", end="")
result = "rocK"
if choice == 2 and comp_choice == 3:
print("Scissors wins =>", end="")
result = "scissoR"
elif choice == 3 and comp_choice == 2:
print("Scissors wins =>", end="")
result = "Rock"
# Printing either user or computer wins or draw
if result == "DRAW":
print("<== Its a tie ==>")
if result == choice_name:
print("<== User wins ==>")
else:
print("<== Computer wins ==>")
print("Do you want to play again? (Y/N)")
# if user input n or N then condition is True
ans = input().lower
if ans == "n":
break
# after coming out of the while loop
# we print thanks for playing
print("thanks for playing")
|
#Output : Winning Rules as follows:
|
Rock Paper Scissor game in Python
# import random module
import random
# print multiline instruction
# performstring concatenation of string
print(
"Winning rules of the game ROCK PAPER SCISSORS are :\n"
+ "Rock vs Paper -> Paper wins \n"
+ "Rock vs Scissors -> Rock wins \n"
+ "Paper vs Scissors -> Scissor wins \n"
)
while True:
print("Enter your choice \n 1 - Rock \n 2 - Paper \n 3 - Scissors \n")
# take the input from user
choice = int(input("Enter your choice :"))
# OR is the short-circuit operator
# if any one of the condition is true
# then it return True value
# looping until user enter invalid input
while choice > 3 or choice < 1:
choice = int(input("Enter a valid choice please ???"))
# initialize value of choice_name variable
# corresponding to the choice value
if choice == 1:
choice_name = "Rock"
elif choice == 2:
choice_name = "Paper"
else:
choice_name = "Scissors"
# print user choice
print("User choice is \n", choice_name)
print("Now its Computers Turn....")
# Computer chooses randomly any number
# among 1 , 2 and 3. Using randint method
# of random module
comp_choice = random.randint(1, 3)
# looping until comp_choice value
# is equal to the choice value
while comp_choice == choice:
comp_choice = random.randint(1, 3)
# initialize value of comp_choice_name
# variable corresponding to the choice value
if comp_choice == 1:
comp_choice_name = "rocK"
elif comp_choice == 2:
comp_choice_name = "papeR"
else:
comp_choice_name = "scissoR"
print("Computer choice is \n", comp_choice_name)
print(choice_name, "Vs", comp_choice_name)
# we need to check of a draw
if choice == comp_choice:
print("Its a Draw", end="")
result = "DRAW"
# condition for winning
if choice == 1 and comp_choice == 2:
print("paper wins =>", end="")
result = "papeR"
elif choice == 2 and comp_choice == 1:
print("paper wins =>", end="")
result = "Paper"
if choice == 1 and comp_choice == 3:
print("Rock wins =>\n", end="")
result = "Rock"
elif choice == 3 and comp_choice == 1:
print("Rock wins =>\n", end="")
result = "rocK"
if choice == 2 and comp_choice == 3:
print("Scissors wins =>", end="")
result = "scissoR"
elif choice == 3 and comp_choice == 2:
print("Scissors wins =>", end="")
result = "Rock"
# Printing either user or computer wins or draw
if result == "DRAW":
print("<== Its a tie ==>")
if result == choice_name:
print("<== User wins ==>")
else:
print("<== Computer wins ==>")
print("Do you want to play again? (Y/N)")
# if user input n or N then condition is True
ans = input().lower
if ans == "n":
break
# after coming out of the while loop
# we print thanks for playing
print("thanks for playing")
#Output : Winning Rules as follows:
[END]
|
Taking Screenshots using pyscreenshot in Python
|
https://www.geeksforgeeks.org/taking-screenshots-using-pyscreenshot-in-python/
|
# Program to take screenshot
import pyscreenshot
# To capture the screen
image = pyscreenshot.grab()
# To display the captured screenshot
image.show()
# To save the screenshot
image.save("GeeksforGeeks.png")
|
#Output : pip install pyscreenshot
|
Taking Screenshots using pyscreenshot in Python
# Program to take screenshot
import pyscreenshot
# To capture the screen
image = pyscreenshot.grab()
# To display the captured screenshot
image.show()
# To save the screenshot
image.save("GeeksforGeeks.png")
#Output : pip install pyscreenshot
[END]
|
Taking Screenshots using pyscreenshot in Python
|
https://www.geeksforgeeks.org/taking-screenshots-using-pyscreenshot-in-python/
|
# Program for partial screenshot
import pyscreenshot
# im=pyscreenshot.grab(bbox=(x1,x2,y1,y2))
image = pyscreenshot.grab(bbox=(10, 10, 500, 500))
# To view the screenshot
image.show()
# To save the screenshot
image.save("GeeksforGeeks.png")
|
#Output : pip install pyscreenshot
|
Taking Screenshots using pyscreenshot in Python
# Program for partial screenshot
import pyscreenshot
# im=pyscreenshot.grab(bbox=(x1,x2,y1,y2))
image = pyscreenshot.grab(bbox=(10, 10, 500, 500))
# To view the screenshot
image.show()
# To save the screenshot
image.save("GeeksforGeeks.png")
#Output : pip install pyscreenshot
[END]
|
Desktop Notifier in Python
|
https://www.geeksforgeeks.org/desktop-notifier-python/
|
import requests
import xml.etree.ElementTree as ET
# url of news rss feed
RSS_FEED_URL = "http://www.hindustantimes.com/rss/topnews/rssfeed.xml"
def loadRSS():
"""
utility function to load RSS feed
"""
# create HTTP request response object
resp = requests.get(RSS_FEED_URL)
# return response content
return resp.content
def parseXML(rss):
"""
utility function to parse XML format rss feed
"""
# create element tree root object
root = ET.fromstring(rss)
# create empty list for news items
newsitems = []
# iterate news items
for item in root.findall("./channel/item"):
news = {}
# iterate child elements of item
for child in item:
# special checking for namespace object content:media
if child.tag == "{http://search.yahoo.com/mrss/}content":
news["media"] = child.attrib["url"]
else:
news[child.tag] = child.text.encode("utf8")
newsitems.append(news)
# return news items list
return newsitems
def topStories():
"""
main function to generate and return news items
"""
# load rss feed
rss = loadRSS()
# parse XML
newsitems = parseXML(rss)
return newsitems
|
#Output : {'description': 'Months after it was first reported, the feud between Dwayne Johnson and
|
Desktop Notifier in Python
import requests
import xml.etree.ElementTree as ET
# url of news rss feed
RSS_FEED_URL = "http://www.hindustantimes.com/rss/topnews/rssfeed.xml"
def loadRSS():
"""
utility function to load RSS feed
"""
# create HTTP request response object
resp = requests.get(RSS_FEED_URL)
# return response content
return resp.content
def parseXML(rss):
"""
utility function to parse XML format rss feed
"""
# create element tree root object
root = ET.fromstring(rss)
# create empty list for news items
newsitems = []
# iterate news items
for item in root.findall("./channel/item"):
news = {}
# iterate child elements of item
for child in item:
# special checking for namespace object content:media
if child.tag == "{http://search.yahoo.com/mrss/}content":
news["media"] = child.attrib["url"]
else:
news[child.tag] = child.text.encode("utf8")
newsitems.append(news)
# return news items list
return newsitems
def topStories():
"""
main function to generate and return news items
"""
# load rss feed
rss = loadRSS()
# parse XML
newsitems = parseXML(rss)
return newsitems
#Output : {'description': 'Months after it was first reported, the feud between Dwayne Johnson and
[END]
|
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