Update app.py

app.py

@@ -4,60 +4,84 @@ import random
 import plotly.graph_objects as go
 import plotly.express as px
 
-def health_game():
-    # Define the states and conditions of interest
-    states = ["Minnesota", "Florida", "California"]
-    top_n = 10
+def generate_health_conditions():
+    return [
+        {"condition": "💔 Heart disease", "emoji": "💗", "spending": {"Minnesota": 100, "Florida": 150, "California": 200, "New York": 120, "Texas": 180}, "treatment": "Regular checkups with a cardiologist", "savings": "$1000"},
+        {"condition": "🤕 Trauma-related disorders", "emoji": "🚑", "spending": {"Minnesota": 90, "Florida": 110, "California": 150, "New York": 100, "Texas": 130}, "treatment": "Counseling and physical therapy", "savings": "$500"},
+        {"condition": "🦀 Cancer", "emoji": "🎗️", "spending": {"Minnesota": 80, "Florida": 120, "California": 180, "New York": 100, "Texas": 150}, "treatment": "Early detection and treatment", "savings": "$2000"},
+        {"condition": "🧠 Mental disorders", "emoji": "🧘", "spending": {"Minnesota": 70, "Florida": 100, "California": 140, "New York": 90, "Texas": 120}, "treatment": "Therapy and medication", "savings": "$1500"},
+        {"condition": "🦴 Osteoarthritis and joint disorders", "emoji": "🏥", "spending": {"Minnesota": 60, "Florida": 90, "California": 120, "New York": 80, "Texas": 100}, "treatment": "Low-impact exercise and physical therapy", "savings": "$800"},
+        {"condition": "💉 Diabetes", "emoji": "🩸", "spending": {"Minnesota": 50, "Florida": 80, "California": 100, "New York": 60, "Texas": 90}, "treatment": "Regular checkups and medication", "savings": "$1200"},
+        {"condition": "🫁 Chronic obstructive pulmonary disease and asthma", "emoji": "🫀", "spending": {"Minnesota": 40, "Florida": 70, "California": 90, "New York": 50, "Texas": 80}, "treatment": "Inhalers and breathing exercises", "savings": "$600"},
+        {"condition": "🩺 Hypertension", "emoji": "💉", "spending": {"Minnesota": 30, "Florida": 60, "California": 80, "New York": 40, "Texas": 70}, "treatment": "Lifestyle changes and medication", "savings": "$900"},
+        {"condition": "🔬 Hyperlipidemia", "emoji": "🔬", "spending": {"Minnesota": 20, "Florida": 50, "California": 70, "New York": 30, "Texas": 60}, "treatment": "Lifestyle changes and medication", "savings": "$700"},
+        {"condition": "🦴 Back problems", "emoji": "🧍", "spending": {"Minnesota": 10, "Florida": 40,
+
+                                                                    def calculate_total_spending(health_conditions):
+    total_spending = 0
+    for condition in health_conditions:
+        for state, spending in condition["spending"].items():
+            total_spending += spending
+    return round(total_spending, 1)
 
-    # Define the list dictionary of top 10 health conditions descending by cost, with emojis, treatment recommendation and potential savings
-    health_conditions = [
-        {"condition": "💔 Heart disease", "emoji": "💗", "spending": 214.3, "treatment": "Regular checkups with a cardiologist", "savings": "$1000"},
-        {"condition": "🤕 Trauma-related disorders", "emoji": "🚑", "spending": 198.6, "treatment": "Counseling and physical therapy", "savings": "$500"},
-        {"condition": "🦀 Cancer", "emoji": "🎗️", "spending": 171.0, "treatment": "Early detection and treatment", "savings": "$2000"},
-        {"condition": "🧠 Mental disorders", "emoji": "🧘", "spending": 150.8, "treatment": "Therapy and medication", "savings": "$1500"},
-        {"condition": "🦴 Osteoarthritis and joint disorders", "emoji": "🏥", "spending": 142.4, "treatment": "Low-impact exercise and physical therapy", "savings": "$800"},
-        {"condition": "💉 Diabetes", "emoji": "🩸", "spending": 107.4, "treatment": "Regular checkups and medication", "savings": "$1200"},
-        {"condition": "🫁 Chronic obstructive pulmonary disease and asthma", "emoji": "🫀", "spending": 91.0, "treatment": "Inhalers and breathing exercises", "savings": "$600"},
-        {"condition": "🩺 Hypertension", "emoji": "💉", "spending": 83.9, "treatment": "Lifestyle changes and medication", "savings": "$900"},
-        {"condition": "🔬 Hyperlipidemia", "emoji": "🔬", "spending": 83.9, "treatment": "Lifestyle changes and medication", "savings": "$700"},
-        {"condition": "🦴 Back problems", "emoji": "🧍", "spending": 67.0, "treatment": "Physical therapy and exercise", "savings": "$400"}
-    ]
-
-    # Create a DataFrame from the list dictionary
-    df_top_conditions = pd.DataFrame(health_conditions)
-
-    # Calculate the total spending
-    total_spending = round(df_top_conditions["spending"].sum(), 1)
-
-    # Define the roll function
-    def roll():
-        rolls = [random.randint(1, 10) for _ in range(1000)]
-        frequencies = [rolls.count(i) for i in range(1, 11)]
-        return frequencies
-
-    # Define the sunburst chart
-    fig_sunburst = go.Figure(go.Sunburst(
-        labels=df_top_conditions["emoji"] + " " + df_top_conditions["condition"],
-        parents=[""] * top_n,
-        values=df_top_conditions["spending"],
-        maxdepth=2
+def generate_sunburst_chart(health_conditions, total_spending):
+    fig_sunburst = go.Figure(go.Treemap(
+        labels=[f"{condition['emoji']} {condition['condition']} ({state})" for condition in health_conditions for state in condition['spending'].keys()],
+        parents=[f"{condition['condition']} ({state})" for condition in health_conditions for state in condition['spending'].keys()],
+        values=[spending for condition in health_conditions for spending in condition['spending'].values()],
+        branchvalues="total",
     ))
 
-    # Customize the layout of the sunburst chart
-   
-    fig_sunburst.update_layout(title=f"Top {top_n} Health Conditions in {', '.join(states)} by Spending (Total: ${total_spending}B)")
+    fig_sunburst.update_layout(
+        title=f"Top Health Conditions in Different States by Spending (Total: ${total_spending}B)",
+        margin=dict(l=0, r=0, t=50, b=0),
+    )
+    return fig_sunburst
+
+def roll(state, condition):
+    frequencies = [random.randint(1, 10) for _ in range(1000)]
+    spending = condition["spending"][state]
+    frequencies = [round(frequency * spending / 100, 1) for frequency in frequencies]
+    return frequencies
+
+def generate_bar_chart(state, condition, frequencies):
+    fig_bar = px.bar(
+        x=[f"Variant {i}" for i in range(1, 11)],
+        y=frequencies[:10],
+        labels={'x': 'Variant', 'y': 'Cost'},
+        title=f"Variants of {condition['condition']} ({condition['emoji']}) in {state}",
+    )
+    return fig_bar
+
+def generate_recommendation(condition):
+    return f"Based on the severity of your {condition['condition']}, we recommend {condition['treatment']} for early treatment. This could save you up to {condition['savings']} in healthcare costs."
+
+def main():
+    states = ["Minnesota", "Florida", "California", "New York", "Texas"]
+    top_n = 10
+
+    health_conditions = generate_health_conditions()
+
+    total_spending = calculate_total_spending(health_conditions)
+
+    fig_sunburst = generate_sunburst_chart(health_conditions, total_spending)
 
-    # Display the sunburst chart and variants per condition in the Streamlit app
     st.plotly_chart(fig_sunburst)
-    condition_idx = st.selectbox("Select your current health condition", df_top_conditions.index)
-    row = df_top_conditions.loc[condition_idx]
 
-    st.write(f"Based on the severity of your {row['condition']}, we recommend {row['treatment']} for early treatment. This could save you up to {row['savings']} in healthcare costs.")
+    condition_idx = st.selectbox("Select your current health condition", range(top_n))
+
+    condition = health_conditions[condition_idx]
+
+    st.write(generate_recommendation(condition))
+
+    state = st.selectbox("Select your state", states)
+
+    frequencies = roll(state, condition)
+
+    fig_bar = generate_bar_chart(state, condition, frequencies)
 
-    frequencies = roll()
-    fig_bar = px.bar(x=[f"Variant {i}" for i in range(1, 11)], y=frequencies[:10], labels={'x': 'Variant', 'y': 'Frequency'})
-    fig_bar.update_layout(title=f"Variants of {row['condition']} ({row['emoji']})")
     st.plotly_chart(fig_bar)
 
+if __name__ == "__main__":
+    main()
 
-health_game()