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import gradio as gr |
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import pandas as pd |
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import plotly.express as px |
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def load_data(): |
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df = pd.DataFrame({ |
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"tax_type": ["Income Tax", "Sales Tax", "Property Tax", "Corporate Tax", "Value Added Tax (VAT)", |
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"Income Tax", "Sales Tax", "Property Tax", "Corporate Tax", "Value Added Tax (VAT)"], |
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"compliance": [0.75, 0.82, 0.60, 0.70, 0.65, |
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0.79, 0.75, 0.66, 0.72, 0.68] |
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}) |
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return df |
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def compliance_analysis(tax_type): |
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df = load_data() |
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compliance_rate = df[df["tax_type"] == tax_type]["compliance"].mean() |
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compliance_rate = round(compliance_rate * 100, 2) |
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df = df.groupby("tax_type").mean().reset_index() |
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df = df.sort_values("compliance", ascending=False) |
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fig = px.bar(df, x="compliance", y="tax_type", color="tax_type", orientation="h", |
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title="Average Compliance Rate for Tax Types", |
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labels={"compliance": "Compliance Rate (%)", "tax_type": "Tax Type"}) |
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fig.update_xaxes(ticktext=[str(round(v * 100, 2)) + "%" for v in df["compliance"]], |
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tickvals=df["compliance"] * 100) |
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fig.update_layout(shapes=[ |
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dict(type='line', x0=compliance_rate, x1=compliance_rate, y0=0, y1=1, yref='paper', |
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line=dict(color='red', dash='dash')), |
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dict(type='text', x=compliance_rate, y=1.1, yref='paper', |
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text=f"{tax_type} ({compliance_rate}%)", textangle=0, font=dict(color='red', size=12)) |
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]) |
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return fig |
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tax_types = ["Income Tax", "Sales Tax", "Property Tax", "Corporate Tax", "Value Added Tax (VAT)"] |
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inputs = gr.components.Dropdown(tax_types, default=tax_types[0], label="Tax Type") |
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outputs = gr.components.PlotlyPlot(label="Compliance Rate") |
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gr.Interface(fn=compliance_analysis, inputs=inputs, outputs=outputs, title="Compliance Analysis", iframe_height=300).launch() |
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