feat: updated app.py

app.py

@@ -244,8 +244,23 @@ elif page == "Customer Analysis":
                     sales_data_filtered = sales_data.drop(index='CLIENTE', errors='ignore')
                     sales_data_filtered = sales_data_filtered.apply(pd.to_numeric, errors='coerce')
 
-                    top_units = all_manufacturers.sort_values(by=all_manufacturers.columns[0], ascending=False).head(10)
-                    top_sales = sales_data_filtered.sort_values(by=sales_data_filtered.columns[0], ascending=False).head(10)
+                    # Ensure the values in all_manufacturers are numeric before sorting
+                    all_manufacturers_numeric = pd.to_numeric(all_manufacturers.iloc[:, 0], errors='coerce')
+
+                    # Sort the manufacturers based on numeric values
+                    top_units = all_manufacturers.assign(numeric_values=all_manufacturers_numeric).sort_values(by='numeric_values', ascending=False).head(10)
+
+                    # Drop the temporary numeric column after sorting
+                    top_units = top_units.drop(columns=['numeric_values'])
+
+                    # Ensure the values in sales_data_filtered are numeric before sorting
+                    sales_data_filtered_numeric = pd.to_numeric(sales_data_filtered.iloc[:, 0], errors='coerce')
+
+                    # Sort the sales data based on numeric values
+                    top_sales = sales_data_filtered.assign(numeric_values=sales_data_filtered_numeric).sort_values(by='numeric_values', ascending=False).head(10)
+
+                    # Drop the temporary numeric column after sorting
+                    top_sales = top_sales.drop(columns=['numeric_values'])
                     combined_top = pd.concat([top_units, top_sales]).index.unique()[:20]
                     combined_top = [m for m in combined_top if m in all_manufacturers.index and m in sales_data_filtered.index]