Create backupapp.py

backupapp.py

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+import streamlit as st
+import plotly.express as px
+import pandas as pd
+
+# Define the states and conditions of interest
+states = ["Minnesota", "Florida", "California"]
+top_n = 10
+
+# Define the list dictionary of top 10 health conditions descending by cost
+health_conditions = [
+    {"condition": "Heart disease", "spending": 214.3},
+    {"condition": "Trauma-related disorders", "spending": 198.6},
+    {"condition": "Cancer", "spending": 171.0},
+    {"condition": "Mental disorders", "spending": 150.8},
+    {"condition": "Osteoarthritis and joint disorders", "spending": 142.4},
+    {"condition": "Diabetes", "spending": 107.4},
+    {"condition": "Chronic obstructive pulmonary disease and asthma", "spending": 91.0},
+    {"condition": "Hypertension", "spending": 83.9},
+    {"condition": "Hyperlipidemia", "spending": 83.9},
+    {"condition": "Back problems", "spending": 67.0}
+]
+
+# Total the spending values
+total_spending = sum([hc["spending"] for hc in health_conditions])
+
+# Create a DataFrame from the list dictionary
+df_top_conditions = pd.DataFrame(health_conditions)
+
+# Create the treemap graph using Plotly Express
+fig = px.treemap(df_top_conditions, path=["condition"], values="spending")
+
+# Set the title of the graph
+fig.update_layout(title=f"Top {top_n} Health Conditions in {', '.join(states)} by Spending (Total: ${total_spending}B)")
+
+# Display the graph in Streamlit
+st.plotly_chart(fig)