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Update app.py
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app.py
CHANGED
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@@ -34,15 +34,10 @@ all_reps = sorted(df['Rep Name'].dropna().unique())
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# === Tab 1: Summary ===
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def generate_summary(date_str):
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day_df = df[df['Date'] == date_str]
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# Active reps and their total stops
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active = day_df.groupby('Rep Name').size().reset_index(name='Total Visits')
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# Detect inactive reps
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active_list = active['Rep Name'].tolist()
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inactive_list = [rep for rep in all_reps if rep not in active_list]
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inactive_df = pd.DataFrame({'Inactive Reps': inactive_list})
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return active, inactive_df
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# === Tab 2: KAMs ===
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@@ -92,7 +87,7 @@ def show_map(date_str, rep):
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fig.update_layout(mapbox_style="open-street-map", title=f"π {rep}'s Route on {date_str}")
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# Final table
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table = subset[[
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'Visit Order', 'Dealership Name', 'Time', 'Time Diff (min)',
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'Type of call', 'Sales or service'
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@@ -104,7 +99,7 @@ def show_map(date_str, rep):
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'Sales or service': 'πΌ Category'
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})
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#
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total_time = round(table['β±οΈ Time Spent'].sum(), 2)
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summary_row = pd.DataFrame([{
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'Visit Order': '',
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@@ -126,18 +121,13 @@ with gr.Blocks() as app:
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date_summary = gr.Dropdown(label="Select Date", choices=sorted(df['Date'].unique(), reverse=True))
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active_table = gr.Dataframe(label="β
Active Reps (with total visits)")
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inactive_table = gr.Dataframe(label="β οΈ Inactive Reps")
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date_summary.change(fn=generate_summary, inputs=date_summary, outputs=[active_table, inactive_table])
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with gr.Tab("π€ KAM's"):
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date_picker.change(fn=get_reps, inputs=date_picker, outputs=rep_picker)
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btn.click(fn=show_map, inputs=[date_picker, rep_picker], outputs=[table, map_plot])
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app.launch()
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# === Tab 1: Summary ===
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def generate_summary(date_str):
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day_df = df[df['Date'] == date_str]
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active = day_df.groupby('Rep Name').size().reset_index(name='Total Visits')
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active_list = active['Rep Name'].tolist()
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inactive_list = [rep for rep in all_reps if rep not in active_list]
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inactive_df = pd.DataFrame({'Inactive Reps': inactive_list})
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return active, inactive_df
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# === Tab 2: KAMs ===
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fig.update_layout(mapbox_style="open-street-map", title=f"π {rep}'s Route on {date_str}")
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# Final table
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table = subset[[
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'Visit Order', 'Dealership Name', 'Time', 'Time Diff (min)',
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'Type of call', 'Sales or service'
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'Sales or service': 'πΌ Category'
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})
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# Add summary row
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total_time = round(table['β±οΈ Time Spent'].sum(), 2)
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summary_row = pd.DataFrame([{
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'Visit Order': '',
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date_summary = gr.Dropdown(label="Select Date", choices=sorted(df['Date'].unique(), reverse=True))
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active_table = gr.Dataframe(label="β
Active Reps (with total visits)")
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inactive_table = gr.Dataframe(label="β οΈ Inactive Reps")
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date_summary.change(fn=generate_summary, inputs=date_summary, outputs=[active_table, inactive_table])
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with gr.Tab("π€ KAM's"):
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with gr.Row():
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with gr.Column(scale=1):
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date_picker = gr.Dropdown(label="Select Date", choices=sorted(df['Date'].unique(), reverse=True))
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rep_picker = gr.Dropdown(label="Select Rep")
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btn = gr.Button("Show Route")
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with gr.Column(scale=2):
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table = gr.Dataframe(label="
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