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import streamlit as st | |
import pandas as pd | |
import numpy as np | |
# Create two datasets | |
hospitals_list = [{"City":"New York","State": "NY","Bed Count":1200},{"City":"Los Angeles","State":"CA","Bed Count":1400},{"City":"Chicago","State":"IL","Bed Count":1650}] | |
state_data = [{"State":"NY","Population": 8.5e6,"Square Miles": 54.556},{"State":"CA","Population": 39.25e6,"Square Miles": 163.696},{"State":"IL","Population": 12.8e6,"Square Miles": 57.914}] | |
# Create dataframes from the datasets | |
hospitals_df = pd.DataFrame(hospitals_list) | |
state_df = pd.DataFrame(state_data) | |
# Merge the two datasets together | |
merged_df = pd.merge(hospitals_df, state_df, on="State") | |
# Display the merged dataset | |
st.write("Merged Dataset") | |
st.write(merged_df) | |
# Calculate average beds per square mile | |
st.write("Calculated Function") | |
st.write(merged_df.loc[:,"Bed Count"]/merged_df.loc[:,"Square Miles"]) |