Create app.py

app.py

@@ -0,0 +1,55 @@
+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()