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Update app.py
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app.py
CHANGED
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@@ -187,7 +187,7 @@ with gr.Blocks(fill_height=True) as demo:
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gr.Markdown("Window = 3-period/months, the predictive model reacts more quickly to recent monthly payment fluctuations, but it may also include more noise.<br><br>Window = 12-period/months, the Forecast adjusts more slowly and is less sensitive to small fluctuations, making it more reliable, but also slower to react to sharp changes.")
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btn_update = gr.Button("Run Forecast")
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gr.HTML(f"<h2>Predictions</h2>")
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gr.Markdown("
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table_1 = gr.DataFrame(value=df, label="Predictions -> consult 'Prediction Revenue' column:")
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#table_2 = gr.DataFrame(value=df_2, label="Forecast Inputs:")
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btn_update.click(fn=update_table, inputs=[start_input, prediction_input, range_input, user_text], outputs=[table_1#,table_2
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gr.Markdown("Window = 3-period/months, the predictive model reacts more quickly to recent monthly payment fluctuations, but it may also include more noise.<br><br>Window = 12-period/months, the Forecast adjusts more slowly and is less sensitive to small fluctuations, making it more reliable, but also slower to react to sharp changes.")
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btn_update = gr.Button("Run Forecast")
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gr.HTML(f"<h2>Predictions</h2>")
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gr.Markdown("Also it's recommended to re-run the predictions after the selected month has passed.")
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table_1 = gr.DataFrame(value=df, label="Predictions -> consult 'Prediction Revenue' column:")
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#table_2 = gr.DataFrame(value=df_2, label="Forecast Inputs:")
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btn_update.click(fn=update_table, inputs=[start_input, prediction_input, range_input, user_text], outputs=[table_1#,table_2
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