[9:16 AM] Wacker, Aaron C
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()