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