Update app.py

app.py

@@ -1,47 +1,17 @@
 import pandas as pd
+import plotly.express as px
 import streamlit as st
-import plotly.graph_objects as go
-import time
-
-def create_sunburst_plot(df):
-    fig = go.Figure(go.Sunburst(
-        labels=df['labels'],
-        parents=df['parents'],
-        values=df['values'],
-        ids=df['ids'],
-        text=df['text'],
-        hoverinfo="label+value",
-        branchvalues="total",
-    ))
-
-    fig.update_layout(margin=dict(t=0, l=0, r=0, b=0))
-    return fig
-
-data = [
-    {'ids': 'Root', 'labels': 'Root', 'parents': '', 'values': None, 'text': 'Root'},
-    {'ids': 'Hip Surgery', 'labels': 'Hip Surgery', 'parents': 'Root', 'values': 30, 'text': 'Hip Surgery'},
-    {'ids': 'Knee Surgery', 'labels': 'Knee Surgery', 'parents': 'Root', 'values': 40, 'text': 'Knee Surgery'},
-    {'ids': 'CPT1', 'labels': 'CPT1', 'parents': 'Hip Surgery', 'values': 20, 'text': 'CPT1'},
-    {'ids': 'CPT2', 'labels': 'CPT2', 'parents': 'Hip Surgery', 'values': 10, 'text': 'CPT2'},
-    {'ids': 'CPT3', 'labels': 'CPT3', 'parents': 'Knee Surgery', 'values': 25, 'text': 'CPT3'},
-    {'ids': 'CPT4', 'labels': 'CPT4', 'parents': 'Knee Surgery', 'values': 15, 'text': 'CPT4'},
-]
 
+# Create a DataFrame with CPT codes, procedures, and expected costs
+data = {
+    'CPT Code': ['99201', '99232', '99233', '99234', '99235'],
+    'Procedure': ['Office/Outpatient Visit', 'Inpatient Consultation', 'Initial Hospital Care', 'Subsequent Hospital Care', 'Critical Care Services'],
+    'Expected Cost': [100, 200, 150, 250, 300]
+}
 df = pd.DataFrame(data)
 
-# Function to update the data
-def update_data(df):
-    # Here you can add your logic to vary the cost data
-    df['values'] = df['values'] + 5
-    return df
-
-# Create a placeholder for the plot
-# animate the chart by incrementing the cost values and updating the chart every second. You can adjust the update_data function to customize the variations in the data.
+# Create a histogram with Plotly Express
+fig = px.histogram(df, x='Procedure', y='Expected Cost')
 
-# Loop to animate
-for i in range(10):  # Loop for 10 iterations
-    df = update_data(df)
-    fig = create_sunburst_plot(df)
-    #st.plot(create_sunburst_plot(df))
-    st.plotly_chart(create_sunburst_plot(df))
-    time.sleep(5)  # Sleep for 5 seconds
+# Display the histogram in Streamlit
+st.plotly_chart(fig)