feat: generated files

app.py

@@ -122,29 +122,33 @@ elif page == "Customer Analysis":
             # Remove the 'CLIENTE' row from sales_data to avoid issues with mixed types
             sales_data_filtered = sales_data.drop(index='CLIENTE', errors='ignore')
 
-            # Ensure all values are numeric (optional, but adds robustness)
+            # Ensure all values are numeric
             sales_data_filtered = sales_data_filtered.apply(pd.to_numeric, errors='coerce')
 
-            # Sort manufacturers by percentage of units and get top 10
-            top_units = all_manufacturers.sort_values(by=all_manufacturers.columns[0], ascending=False).head(10)
+            # Combine manufacturers data
+            combined_data = pd.DataFrame({
+                'units': all_manufacturers[all_manufacturers.columns[0]],
+                'sales': sales_data_filtered[sales_data_filtered.columns[0]]
+            })
 
-            # Sort manufacturers by total sales and get top 10
-            top_sales = sales_data_filtered.sort_values(by=sales_data_filtered.columns[0], ascending=False).head(10)
+            # Sort by units, then by sales
+            combined_data_sorted = combined_data.sort_values(by=['units', 'sales'], ascending=False)
 
-            # Combine top manufacturers from both lists
-            combined_top = pd.concat([top_units, top_sales]).index.unique()
+            # Filter out manufacturers with 0 units
+            non_zero_manufacturers = combined_data_sorted[combined_data_sorted['units'] > 0]
 
-            values = []  # Will store percentages
-            manufacturers = []
-            amounts = []  # Will store total sales
+            # If we have less than 3 non-zero manufacturers, add some zero-value ones
+            if len(non_zero_manufacturers) < 3:
+                zero_manufacturers = combined_data_sorted[combined_data_sorted['units'] == 0].head(3 - len(non_zero_manufacturers))
+                manufacturers_to_show = pd.concat([non_zero_manufacturers, zero_manufacturers])
+            else:
+                manufacturers_to_show = non_zero_manufacturers
 
-            for m in combined_top:
-                if m in all_manufacturers.index and m in sales_data_filtered.index:
-                    values.append(float(all_manufacturers.loc[m, all_manufacturers.columns[0]]))
-                    manufacturers.append(get_supplier_name(m))
-                    amounts.append(float(sales_data_filtered.loc[m, sales_data_filtered.columns[0]]))
+            values = manufacturers_to_show['units'].tolist()
+            amounts = manufacturers_to_show['sales'].tolist()
+            manufacturers = [get_supplier_name(m) for m in manufacturers_to_show.index]
 
-            st.write(f"### Results for top {len(manufacturers)} manufacturers (balanced by units % and total sales):")
+            st.write(f"### Results for top {len(manufacturers)} manufacturers:")
             for manufacturer, value, amount in zip(manufacturers, values, amounts):
                 st.write(f"{manufacturer} = {value:.2f}% of units, €{amount:.2f} total sales")