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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 pandas as pd
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def generate_hospital_data():
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def generate_state_data():
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def merge_datasets(hospitals_df, states_df):
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def calculate_beds_per_capita(merged_df):
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def main():
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if __name__ == "__main__":
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import streamlit as st
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import pandas as pd
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def generate_hospital_data():
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# Generate hospital data
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hospitals = {
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"city": ["New York", "Los Angeles", "Chicago", "Houston", "Phoenix"],
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"state": ["NY", "CA", "IL", "TX", "AZ"],
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"bed_count": [1200, 1500, 1100, 1300, 1400],
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}
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df = pd.DataFrame(hospitals)
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return df
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def generate_state_data():
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# Generate state data
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states = {
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"state": ["NY", "CA", "IL", "TX", "AZ"],
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"population": [20000000, 40000000, 13000000, 29000000, 7000000],
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"square_miles": [54556, 163696, 57914, 268596, 113990],
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}
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df = pd.DataFrame(states)
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return df
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def merge_datasets(hospitals_df, states_df):
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# Merge hospital and state data
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merged_df = pd.merge(hospitals_df, states_df, on="state")
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return merged_df
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def calculate_beds_per_capita(merged_df):
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# Calculate beds per capita
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merged_df["beds_per_capita"] = merged_df["bed_count"] / merged_df["population"]
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return merged_df
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def main():
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# Generate data
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hospitals_df = generate_hospital_data()
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states_df = generate_state_data()
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# Merge datasets
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merged_df = merge_datasets(hospitals_df, states_df)
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# Calculate beds per capita
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merged_df = calculate_beds_per_capita(merged_df)
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# Show merged and calculated data
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st.write(merged_df)
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if __name__ == "__main__":
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main()
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