asistaoptum commited on
Commit
ad3e224
1 Parent(s): c06357b

Create app.py

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first app file

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  1. app.py +37 -0
app.py ADDED
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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()     # Merge datasets
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+     merged_df = merge_datasets(hospitals_df, states_df)     # Calculate beds per capita
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+     merged_df = calculate_beds_per_capita(merged_df)     # 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()