feat: generated files

app.py

@@ -101,40 +101,36 @@ elif page == "Customer Analysis":
         if not customer_data.empty and not customer_euros.empty:
             st.write(f"### Analysis for Customer {customer_code}")
 
-            # Ensure all manufacturer codes are strings
-            all_manufacturers = customer_data.iloc[:, 1:].T[customer_data.iloc[:, 1:].T[customer_data.index[0]] > 0]
+            # Get percentage of units sold for each manufacturer
+            all_manufacturers = customer_data.iloc[:, 1:-2].T  # Exclude CLIENTE and last two columns
             all_manufacturers.index = all_manufacturers.index.astype(str)
             
-            # Convert to numeric and handle any non-numeric values
-            all_manufacturers = all_manufacturers.apply(pd.to_numeric, errors='coerce')
-            customer_euros = customer_euros.apply(pd.to_numeric, errors='coerce')
+            # Get total sales for each manufacturer
+            sales_data = customer_euros.iloc[:, 1:].T  # Exclude CLIENTE column
+            sales_data.index = sales_data.index.astype(str)
 
+            # Sort manufacturers by percentage of units and get top 10
             top_units = all_manufacturers.sort_values(by=customer_data.index[0], ascending=False).head(10)
             
-            # Ensure we're working with numeric data for sorting
-            numeric_euros = customer_euros.select_dtypes(include=[np.number])
-            if not numeric_euros.empty:
-                top_sales = numeric_euros.iloc[0].sort_values(ascending=False).head(10)
-                top_sales.index = top_sales.index.astype(str)
-            else:
-                st.warning("No numeric sales data available for this customer.")
-                top_sales = pd.Series()
+            # Sort manufacturers by total sales and get top 10
+            top_sales = sales_data.sort_values(by=customer_euros.index[0], ascending=False).head(10)
 
+            # Combine top manufacturers from both lists
             combined_top = pd.concat([top_units, top_sales]).index.unique()
 
-            values = []
+            values = []  # Will store percentages
             manufacturers = []
-            amounts = []
+            amounts = []  # Will store total sales
 
             for m in combined_top:
-                if m in all_manufacturers.index and m in customer_euros.columns:
-                    values.append(all_manufacturers[m])
+                if m in all_manufacturers.index and m in sales_data.index:
+                    values.append(all_manufacturers.loc[m, customer_data.index[0]])
                     manufacturers.append(get_supplier_name(m))
-                    amounts.append(customer_euros[m].iloc[0])
+                    amounts.append(sales_data.loc[m, customer_euros.index[0]])
 
-            st.write(f"### Results for top {len(manufacturers)} manufacturers (balanced by units and sales):")
+            st.write(f"### Results for top {len(manufacturers)} manufacturers (balanced by units % and total sales):")
             for manufacturer, value, amount in zip(manufacturers, values, amounts):
-                st.write(f"{manufacturer} = {value:.4f} units, €{amount:.2f}")
+                st.write(f"{manufacturer} = {value:.2f}% of units, €{amount:.2f} total sales")
 
             if manufacturers:  # Only create the chart if we have data
                 fig = radar_chart(manufacturers, values, amounts, f'Radar Chart for Top {len(manufacturers)} Manufacturers of Customer {customer_code}')