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import streamlit as st | |
import pandas as pd | |
# Dataset 1: List of Hospitals that are over 1000 bed count by city and state | |
hospitals = [ | |
{'City': 'New York', 'State': 'NY', 'Hospital Name': 'New York-Presbyterian Hospital', 'Bed Count': 2446}, | |
{'City': 'Houston', 'State': 'TX', 'Hospital Name': 'Memorial Hermann-Texas Medical Center', 'Bed Count': 2048}, | |
{'City': 'Philadelphia', 'State': 'PA', 'Hospital Name': 'Hospital of the University of Pennsylvania', 'Bed Count': 1875}, | |
{'City': 'Los Angeles', 'State': 'CA', 'Hospital Name': 'Cedars-Sinai Medical Center', 'Bed Count': 1434}, | |
{'City': 'Boston', 'State': 'MA', 'Hospital Name': 'Massachusetts General Hospital', 'Bed Count': 1051}, | |
] | |
# Dataset 2: State population size and square miles | |
population = [ | |
{'State': 'CA', 'Population': 39538223, 'Square Miles': 163696}, | |
{'State': 'TX', 'Population': 29145505, 'Square Miles': 268596}, | |
{'State': 'NY', 'Population': 20215751, 'Square Miles': 54555}, | |
{'State': 'FL', 'Population': 21538187, 'Square Miles': 65755}, | |
{'State': 'PA', 'Population': 13002700, 'Square Miles': 46054}, | |
] | |
# Convert the dictionaries into pandas dataframes | |
hospitals_df = pd.DataFrame(hospitals) | |
population_df = pd.DataFrame(population) | |
# Merge the two dataframes using 'State' as the key | |
merged_df = pd.merge(hospitals_df, population_df, on='State') | |
# Join the 'City' and 'State' columns into a single column | |
merged_df['City_State'] = merged_df['City'] + ', ' + merged_df['State'] | |
# Calculate the number of hospital beds per 10,000 people in each city-state | |
merged_df['Beds per 10K People'] = (merged_df['Bed Count'] / merged_df['Population']) * 10000 | |
# Display the final merged dataframe | |
st.write(merged_df) | |