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import gradio as gr |
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import pandas as pd |
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import numpy as np |
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from data_proc import load_equity_data, load_yield_curve_data, load_credit_spread_data |
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from data_proc import plot_treasury_curves, plot_credit_spreads |
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loser_frame, largest_frame = load_equity_data(False) |
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yc_frame = load_yield_curve_data(False) |
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spread_frame = load_credit_spread_data(False) |
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with gr.Blocks() as crisis_dashboard: |
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gr.Markdown("<font size=36><center>Banking Crisis Dashboard</center></font>") |
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with gr.Tab("Bank Performance"): |
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with gr.Row(): |
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with gr.Column(): |
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gr.Markdown("## <center>Worst performing banks</center>") |
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gr.DataFrame(loser_frame) |
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with gr.Column(): |
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gr.Markdown("## <center>Largest bank performance</center>") |
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gr.DataFrame(largest_frame) |
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gr.Markdown("### <center>*performance since 3/8/2023</center>") |
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with gr.Row(): |
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with gr.Column(): |
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gr.Markdown("## Failed banks") |
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gr.DataFrame(pd.DataFrame(list(zip(['SBNY','SIVB'], ['Signature Bank', 'SVB Financial Group'])), columns=['Ticker','Bank Name'])) |
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with gr.Tab("Interest Rates"): |
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with gr.Row(): |
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with gr.Column(): |
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gr.Markdown("## <center>Treasury yield curve</center>") |
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gr.Plot(plot_treasury_curves(yc_frame)) |
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with gr.Column(): |
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gr.Markdown("## <center>Credit spreads</center>") |
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gr.Plot(plot_credit_spreads(spread_frame)) |
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gr.Markdown("### <center>Data Source: FRED</center>") |
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crisis_dashboard.launch() |