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Update app.py
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app.py
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import streamlit as st
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import
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import
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# Define the state populations and family sizes
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state_data = {
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'California': {'population': 39538223, 'family_size': 3.3},
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'Texas': {'population': 29145505, 'family_size': 3.4},
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'Florida': {'population': 21538187, 'family_size': 3.0},
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'New York': {'population': 19849399, 'family_size': 3.1},
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'Minnesota': {'population': 5700671, 'family_size': 2.5},
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'Wisconsin': {'population': 5897473, 'family_size': 2.6},
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}
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# Define the state spending data
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spending_data = {
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'California': {'education': 2500, 'healthcare': 3000, 'transportation': 1500},
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'Texas': {'education': 2000, 'healthcare': 2500, 'transportation': 1000},
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'Florida': {'education': 1500, 'healthcare': 2000, 'transportation': 750},
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'New York': {'education': 3000, 'healthcare': 3500, 'transportation': 2000},
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'Minnesota': {'education': 1000, 'healthcare': 1500, 'transportation': 500},
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'Wisconsin': {'education': 1250, 'healthcare': 1750, 'transportation': 750},
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}
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# Define the emoji icons
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POPULATION_ICON = 'π₯'
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FAMILY_SIZE_ICON = 'π¨βπ©βπ§βπ¦'
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EDUCATION_ICON = 'π«'
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HEALTHCARE_ICON = 'π₯'
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TRANSPORTATION_ICON = 'π'
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def main():
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st.title('State Comparison')
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b64 = base64.b64encode(file.read()).decode('utf-8')
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st.markdown(f'<a href="data:file/csv;base64,{b64}" download="state_data.csv">Download State Data CSV File</a>', unsafe_allow_html=True)
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#
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for state, data in state_data.items():
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st.subheader(f'{POPULATION_ICON} {state}')
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st.write(f'Population: {data["population"]}')
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st.write(f'Family Size: {data["family_size"]}')
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# Display state spending data
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st.header('State Spending')
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for state, data in spending_data.items():
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st.subheader(state)
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st.write(f'{EDUCATION_ICON} Education: {data["education"]}')
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st.write(f'{HEALTHCARE_ICON} Healthcare: {data["healthcare"]}')
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st.write(f'{TRANSPORTATION_ICON} Transportation: {data["transportation"]}')
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import streamlit as st
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import folium
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import numpy as np
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def main():
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st.title('State Comparison')
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b64 = base64.b64encode(file.read()).decode('utf-8')
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st.markdown(f'<a href="data:file/csv;base64,{b64}" download="state_data.csv">Download State Data CSV File</a>', unsafe_allow_html=True)
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# Create a map with pie charts for each state
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m = folium.Map(location=[37.0902, -95.7129], zoom_start=4)
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for state, data in state_data.items():
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lat, lon = get_coordinates(state)
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popup_text = f'<b>{state}</b><br>Population: {data["population"]}<br>Family Size: {data["family_size"]}'
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chart_data = [spending_data[state]['education'], spending_data[state]['healthcare'], spending_data[state]['transportation']]
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chart_labels = ['Education', 'Healthcare', 'Transportation']
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colors = ['blue', 'red', 'green']
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chart = create_pie_chart(chart_data, chart_labels, colors)
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folium.Marker(location=[lat, lon], popup=popup_text, icon=folium.Icon(color='gray', icon='info-sign')).add_to(m)
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folium.Marker(location=[lat, lon], icon=folium.Icon(color='cadetblue', icon='chart-pie'), tooltip='Click for chart').add_to(m).add_child(chart)
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st.markdown(folium_map_to_html(m), unsafe_allow_html=True)
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def get_coordinates(state):
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# Replace this with your own function to get the coordinates for each state
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# This is just a placeholder
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return np.random.randint(-120, -70), np.random.randint(25, 50)
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def create_pie_chart(data, labels, colors):
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chart = folium.plugins.PieChart(data, labels=labels, colors=colors, radius=30, weight=0.5)
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return chart
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def folium_map_to_html(m):
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return m.get_root().render()
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