Update app.py

app.py

@@ -1,58 +1,14 @@
-import streamlit as st
-import pandas as pd
-import random
-import plotly.graph_objects as go
-import plotly.express as px
-
-# 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, with emojis
-health_conditions = [
-    {"condition": "💔 Heart disease", "emoji": "💗", "spending": 214.3},
-    {"condition": "🤕 Trauma-related disorders", "emoji": "🚑", "spending": 198.6},
-    {"condition": "🦀 Cancer", "emoji": "🎗️", "spending": 171.0},
-    {"condition": "🧠 Mental disorders", "emoji": "🧘", "spending": 150.8},
-    {"condition": "🦴 Osteoarthritis and joint disorders", "emoji": "🏥", "spending": 142.4},
-    {"condition": "💉 Diabetes", "emoji": "🩸", "spending": 107.4},
-    {"condition": "🫁 Chronic obstructive pulmonary disease and asthma", "emoji": "🫀", "spending": 91.0},
-    {"condition": "🩺 Hypertension", "emoji": "💉", "spending": 83.9},
-    {"condition": "🔬 Hyperlipidemia", "emoji": "🔬", "spending": 83.9},
-    {"condition": "🦴 Back problems", "emoji": "🧍", "spending": 67.0}
-]
-
-# Create a DataFrame from the list dictionary
+import streamlit as st, pandas as pd, random, plotly.graph_objects as go, plotly.express as px
+states, top_n = ["Minnesota", "Florida", "California"], 10
+health_conditions = [{"condition": "💔 Heart disease", "emoji": "💗", "spending": 214.3}, {"condition": "🤕 Trauma-related disorders", "emoji": "🚑", "spending": 198.6}, {"condition": "🦀 Cancer", "emoji": "🎗️", "spending": 171.0}, {"condition": "🧠 Mental disorders", "emoji": "🧘", "spending": 150.8}, {"condition": "🦴 Osteoarthritis and joint disorders", "emoji": "🏥", "spending": 142.4}, {"condition": "💉 Diabetes", "emoji": "🩸", "spending": 107.4}, {"condition": "🫁 Chronic obstructive pulmonary disease and asthma", "emoji": "🫀", "spending": 91.0}, {"condition": "🩺 Hypertension", "emoji": "💉", "spending": 83.9}, {"condition": "🔬 Hyperlipidemia", "emoji": "🔬", "spending": 83.9}, {"condition": "🦴 Back problems", "emoji": "🧍", "spending": 67.0}]
 df_top_conditions = pd.DataFrame(health_conditions)
-
-# Calculate the total spending
 total_spending = round(df_top_conditions["spending"].sum(), 1)
-
-# Define the reroll function
-def reroll():
-    # Randomly select a health condition from the top 10
-    index = random.randint(0, 9)
-    condition = df_top_conditions.loc[index, "condition"]
-    emoji = df_top_conditions.loc[index, "emoji"]
-    spending = df_top_conditions.loc[index, "spending"]
-    # Print the condition and ask the user if they want to reroll
-    st.write(f"You rolled: {emoji} {condition} (spending: ${spending}B)")
-    reroll = st.button("Reroll")
-    # If the user clicks the reroll button, call the reroll function again
-    if reroll:
-        reroll()
-
-# 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
-))
-
-# Customize the layout of the sunburst chart
+def roll(): return [random.randint(1, 10) for _ in range(1000)]
+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))
 fig_sunburst.update_layout(title=f"Top {top_n} Health Conditions in {', '.join(states)} by Spending (Total: ${total_spending}B)")
-
-# Display the sunburst chart and reroll button in the Streamlit app
 st.plotly_chart(fig_sunburst)
-st.button("Reroll", on_click=reroll)
+for index, row in df_top_conditions.iterrows():
+    frequencies = roll()
+    fig_bar = px.bar(x=[f"Variant {i}" for i in range(1, 11)], y=frequencies, labels={'x': 'Variant', 'y': 'Frequency'})
+    fig_bar.update_layout(title=f"Variants of {row['condition']} ({row['emoji']})")
+    st.plotly_chart(fig_bar)