feat: Added about section underneath table in col 3

app.py

@@ -254,8 +254,8 @@ if page == "📃 Resumen":
         st.dataframe(ventas_top_100[['codigo_cliente', 'total_sales']],
                     column_order=("codigo_cliente", "total_sales"),
                     hide_index=True,
-                    width=450,  # Ajustar el ancho de la tabla
-                    height=600,  # Ajustar la altura de la tabla
+                    width=350,  # Ajustar el ancho de la tabla
+                    height=400,  # Ajustar la altura de la tabla
                     column_config={
                         "codigo_cliente": st.column_config.TextColumn(
                             "Código de Cliente",
@@ -267,6 +267,23 @@ if page == "📃 Resumen":
                             max_value=ventas_top_100['total_sales'].max()
                         )}
                     )
+        # Calculate sales insights
+        sales_min = ventas_top_100['total_sales'].min()
+        sales_max = ventas_top_100['total_sales'].max()
+        sales_median = ventas_top_100['total_sales'].median()
+        sales_90th = ventas_top_100['total_sales'].quantile(0.9)
+        sales_10th = ventas_top_100['total_sales'].quantile(0.1)
+
+        # About Section with relevant data insights
+        with st.expander('About', expanded=True):
+            st.write(f'''
+                - **Data source**: Internal sales data (Top 100 clients).
+                - **Sales Range**: €{sales_min:,.0f} - €{sales_max:,.0f}.
+                - **Median Sales**: €{sales_median:,.0f}.
+                - **90th Percentile**: €{sales_90th:,.0f}.
+                - **10th Percentile**: €{sales_10th:,.0f}.
+                - This table displays the top 100 clients based on total sales from 2021 to 2023.
+            ''')
 # Customer Analysis Page
 elif page == "🕵️ Análisis de Cliente":
     st.markdown("""