Update app.py

app.py

@@ -1,51 +1,36 @@
 import streamlit as st
-from graphviz import Digraph
+import plotly.express as px
+import pandas as pd
 
-st.set_page_config(page_title="Ideal Care Plan for Top 10 Health Conditions")
+# 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},
+    {"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}
 ]
 
-urls = {
-    "Heart disease ❤️": "https://www.cdc.gov/heartdisease",
-    "Trauma-related disorders 🤕": "https://www.nimh.nih.gov/health/topics/post-traumatic-stress-disorder-ptsd/index.shtml",
-    "Cancer 🦀": "https://www.cancer.gov/",
-}
+# Total the spending values
+total_spending = sum([hc["spending"] for hc in health_conditions])
 
-dot = Digraph(comment="Ideal Care Plan for Top 10 Health Conditions")
-dot.graph_attr["rankdir"] = "LR"
-for condition in health_conditions:
-    name = condition["condition"]
-    spending = condition["spending"]
-    if name in urls:
-        url = urls[name]
-        dot.node(name, f"{name}\n${spending:.1f}B", href=url)
-    else:
-        dot.node(name, f"{name}\n${spending:.1f}B")
+# Create a DataFrame from the list dictionary
+df_top_conditions = pd.DataFrame(health_conditions)
 
-dot.edges([
-    ("Heart disease ❤️", "Hypertension 🩺"),
-    ("Heart disease ❤️", "Hyperlipidemia 🍔"),
-    ("Trauma-related disorders 🤕", "Mental disorders 🧠"),
-    ("Cancer 🦀", "Heart disease ❤️"),
-    ("Cancer 🦀", "Trauma-related disorders 🤕"),
-    ("Cancer 🦀", "Osteoarthritis and joint disorders 🦴"),
-    ("Mental disorders 🧠", "Heart disease ❤️"),
-    ("Mental disorders 🧠", "Trauma-related disorders 🤕"),
-    ("Osteoarthritis and joint disorders 🦴", "Back problems 👨‍⚕️"),
-    ("Diabetes 🍬", "Heart disease ❤️"),
-    ("Diabetes 🍬", "Hypertension 🩺"),
-    ("Chronic obstructive pulmonary disease and asthma 🫁", "Heart disease ❤️"),
-])
+# Create the treemap graph using Plotly Express
+fig = px.treemap(df_top_conditions, path=["condition"], values="spending")
 
-st.graphviz_chart(dot.pipe(format="svg"))
+# 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)