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import streamlit as st
import pandas as pd
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
# 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
))
# 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)")
# 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.")
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)
health_game() |