app.py

import streamlit as st
import pandas as pd
import plotly.express as px

def load_data():
    df = pd.DataFrame({
        "tax_type": ["Income Tax", "Sales Tax", "Property Tax", "Corporate Tax", "Value Added Tax (VAT)",
                     "Income Tax", "Sales Tax", "Property Tax", "Corporate Tax", "Value Added Tax (VAT)"],
        "compliance": [0.75, 0.82, 0.60, 0.70, 0.65,
                       0.79, 0.75, 0.66, 0.72, 0.68]
    })
    return df


def compliance_analysis(tax_type):
    df = load_data()
    
    compliance_rate = df[df["tax_type"] == tax_type]["compliance"].mean()
    compliance_rate = round(compliance_rate * 100, 2)
    
    df = df.groupby("tax_type").mean().reset_index()
    df = df.sort_values("compliance", ascending=False)
    
    fig = px.bar(df, x="compliance", y="tax_type", color="tax_type", orientation="h",
                 title="Average Compliance Rate for Tax Types",
                 labels={"compliance": "Compliance Rate (%)", "tax_type": "Tax Type"})
    
    fig.update_xaxes(ticktext=[str(round(v * 100, 2)) + "%" for v in df["compliance"]],
                     tickvals=df["compliance"] * 100)
    fig.update_layout(shapes=[
        dict(type='line', x0=compliance_rate, x1=compliance_rate, y0=0, y1=1, yref='paper',
             line=dict(color='red', dash='dash')),
        dict(type='text', x=compliance_rate, y=1.1, yref='paper',
             text=f"{tax_type} ({compliance_rate}%)", textangle=0, font=dict(color='red', size=12))
    ])
    
    return fig

tax_types = ["Income Tax", "Sales Tax", "Property Tax", "Corporate Tax", "Value Added Tax (VAT)"]
selected_tax_type = st.selectbox("Select a tax type:", tax_types, index=0)

st.plotly_chart(compliance_analysis(selected_tax_type))