rearrange, add more text stats

app.py

@@ -98,9 +98,13 @@ def full_report():
         df = cached_report.copy(deep=True)
 
     total_jumps = int(df['jumps'].sum())
-    print(f"Total jumps: {total_jumps}")
+    unique_countries = df['country'].nunique()
+    unique_cities = df['city'].nunique()
+
+    print(f"Total jumps: {total_jumps}, unique countries: {unique_countries}, unique cities: {unique_cities}")
     df['iso'] = df['iso'].map(alpha_2_map)
     df['jumps'] = df['jumps'].astype(int)
+    df['city'] = df.apply(lambda row: row['city'] if row['country'] != 'Bermuda' else 'Hamilton', axis=1)
     
     country_df = df.groupby(['country', 'iso']).sum().reset_index()
     country_df = country_df.sort_values(by=['jumps'], ascending=False)
@@ -127,7 +131,7 @@ def full_report():
     city_df = city_df[city_df['city'] != '(not set)']
     city_df['city'] = city_df.apply(lambda row: row['city'] + ', ' + row['iso'], axis=1)
     city_df = city_df[city_df['city'].isin(top_10_cities)].reset_index(drop=True)
-    city_df = city_df.sort_values(by=['jumps'], ascending=True)
+    city_df = city_df.sort_values(by=['day', 'jumps'], ascending=True)
 
     avg = px.bar(city_df, 
                  y='city', x='jumps', color='day',
@@ -189,7 +193,7 @@ def full_report():
                               trendline_scope='overall',
                               template="plotly_dark")
 
-    return f"# Total Jumps: {total_jumps:,}", total, avg, total_map, jumps_over_time, county_map, per_day_plot
+    return f"# {total_jumps:,} total jumps in {unique_cities:,} cities across {unique_countries:,} countries", total, avg, total_map, jumps_over_time, county_map, per_day_plot
 
 
 with gr.Blocks(theme='WeixuanYuan/Soft_dark') as demo:
@@ -197,16 +201,16 @@ with gr.Blocks(theme='WeixuanYuan/Soft_dark') as demo:
         total_jumps_label = gr.Markdown("Total Jumps: 0")
     with gr.Row():
         map_fig = gr.Plot(label="Map")
-    with gr.Row():
-        county_map = gr.Plot(label="US Map")
-    with gr.Row():
-        per_day_plot = gr.Plot(label="Jumps per Day")
     with gr.Row():
         jumps_over_time = gr.Plot(label="Jumps Over Time")
     with gr.Row():
         total_plot = gr.Plot(label="Top 10 Countries")
     with gr.Row():
         avg_plot = gr.Plot(label="Top 10 Cities")
+    with gr.Row():
+        per_day_plot = gr.Plot(label="Jumps per Day")
+    with gr.Row():
+        county_map = gr.Plot(label="US Map")
 
     outputs = [total_jumps_label, total_plot, avg_plot, map_fig, jumps_over_time, county_map, per_day_plot]
     dep = demo.load(full_report, None, outputs)