File size: 5,006 Bytes
644244b 7c9de0c d092073 7c9de0c d092073 06c55ed 51dae36 635f998 51dae36 635f998 51dae36 635f998 51dae36 83d8ab2 51dae36 06c55ed 7c9de0c 3ea6fd9 7c9de0c 40770db 644244b 40770db 644244b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 |
import streamlit as st
import streamlit.components.v1 as components
import networkx as nx
import matplotlib.pyplot as plt
from pyvis.network import Network
import got
import numpy as np
import pandas as pd
import time
import re
import graphviz as graphviz
import pydeck as pdk
from st_click_detector import click_detector
st.graphviz_chart('''
digraph {
PR0001INCOME -> AbleToBuyOnlyNecessities
PR0001INCOME -> DifficultyBuyingNecessities
PR0001INCOME -> DifficultyWithMoneyManagement
PR0001INCOME -> LowNoIncome
PR0001INCOME -> UninsuredMedicalExpenses
}
''')
st.graphviz_chart('''
digraph {
PR0012MENTALHEALTH -> Apprehension -> Undefined -> Fear -> Anxious
PR0012MENTALHEALTH -> Attempts -> Suicide -> Homicide
PR0012MENTALHEALTH -> Difficulty -> Managing -> Anger
PR0012MENTALHEALTH -> Difficulty -> Managing -> Stress
PR0012MENTALHEALTH -> Expresses -> Suicidal -> Homicidal -> Thoughts
PR0012MENTALHEALTH -> False -> Beliefs -> Delusions
PR0012MENTALHEALTH -> False -> Perceptions -> Hallucinations -> Illusions
PR0012MENTALHEALTH -> FlatAffect -> LackofEmotion
PR0012MENTALHEALTH -> Irritable -> Agitated -> Aggressive
PR0012MENTALHEALTH -> LossofInterest -> Involvementin -> ActivitiesSelfCare
PR0012MENTALHEALTH -> MoodSwings
PR0012MENTALHEALTH -> Narrowedto -> Scattered -> Attention -> Focus
PR0012MENTALHEALTH -> Purposeless -> Compulsive -> RepetitiveActivity
PR0012MENTALHEALTH -> Sadness -> Hopelessness -> Decreased -> SelfEsteem
PR0012MENTALHEALTH -> Somatic -> Complaints -> Fatigue
}
''')
st.graphviz_chart('''
digraph {
PR0028RESPIRATION -> Abnormal -> BreathSoundsCrackles
PR0028RESPIRATION -> Abnormal -> IrregularBreathPatterns
PR0028RESPIRATION -> Abnormal -> RespiratoryLaboratoryResults
PR0028RESPIRATION -> Abnormal -> Sputum
PR0028RESPIRATION -> Cough
PR0028RESPIRATION -> Noisy -> RespirationswheezingRalesRhonchi
PR0028RESPIRATION -> Rhinorrhea -> NasalCongestion
PR0028RESPIRATION -> UnabletoBreathe -> Independently
}
''')
st.graphviz_chart('''
digraph {
PR0029CIRCULATION -> Abnormal -> BloodPressureReading
PR0029CIRCULATION -> Abnormal -> CardiacLaboratoryResults
PR0029CIRCULATION -> Abnormal -> Clotting
PR0029CIRCULATION -> Abnormal -> HeartSoundsMurmurs
PR0029CIRCULATION -> Anginal -> Pain
PR0029CIRCULATION -> Cramping -> Pain -> ofExtremities
PR0029CIRCULATION -> Decreased -> Pulses
PR0029CIRCULATION -> Discoloration -> ofSkinCyanosis
PR0029CIRCULATION -> EdemaSwelling -> inlegsarmsfeet
PR0029CIRCULATION -> ExcessivelyRapid -> HeartRate
PR0029CIRCULATION -> IrregularHeartRate
PR0029CIRCULATION -> SyncopalEpisodes -> Fainting -> Dizziness
PR0029CIRCULATION -> TemperatureChange -> inAffectedArea
PR0029CIRCULATION -> Varicosities
}
''')
df = pd.read_csv("testfile.csv")
@st.cache
def convert_df(df):
return df.to_csv().encode('utf-8')
csv = convert_df(df)
st.download_button(
"Press to Download",
csv,
"testfile.csv",
"text/csv",
key='download-csv'
)
st.title('Streamlit Visualization')
dataframe = pd.DataFrame(np.random.randn(10, 20),
columns = ('col %d' % i
for i in range(20)))
st.write(dataframe)
dataframe = pd.DataFrame(np.random.randn(10, 5),
columns = ('col %d' % i
for i in range(5)))
dataframe
st.write('This is a line_chart.')
st.line_chart(dataframe)
st.write('This is a area_chart.')
st.area_chart(dataframe)
st.write('This is a bar_chart.')
st.bar_chart(dataframe)
st.write('Map data')
data_of_map = pd.DataFrame(
np.random.randn(1000, 2) / [60, 60] + [36.66, -121.6],
columns = ['latitude', 'longitude'])
st.map(data_of_map)
image = Image.open('picture.jpg')
st.image(image, caption = 'This is a picture', use_column_width = True)
st.title('Pyvis VisJS DOTlang Legend')
Network(notebook=True)
# make Network show itself with repr_html
def net_repr_html(self):
nodes, edges, height, width, options = self.get_network_data()
html = self.template.render(height=height, width=width, nodes=nodes, edges=edges, options=options)
return html
Network._repr_html_ = net_repr_html
st.sidebar.title('Choose your favorite Graph')
option=st.sidebar.selectbox('select graph',('Simple','Karate', 'GOT'))
physics=st.sidebar.checkbox('add physics interactivity?')
got.simple_func(physics)
if option=='Simple':
HtmlFile = open("test.html", 'r', encoding='utf-8')
source_code = HtmlFile.read()
components.html(source_code, height = 900,width=900)
got.got_func(physics)
if option=='GOT':
HtmlFile = open("gameofthrones.html", 'r', encoding='utf-8')
source_code = HtmlFile.read()
components.html(source_code, height = 1200,width=1000)
got.karate_func(physics)
if option=='Karate':
HtmlFile = open("karate.html", 'r', encoding='utf-8')
source_code = HtmlFile.read()
components.html(source_code, height = 1200,width=1000) |