feat: generated files

app.py

@@ -125,8 +125,8 @@ elif page == "Customer Analysis":
             # Get all manufacturers the customer bought from (ignore the customer column)
             all_manufacturers = customer_data.iloc[:, 1:].T[customer_data.iloc[:, 1:].T[customer_data.index[0]] > purchase_threshold]
             
-            # Sort manufacturers by value in descending order
-            all_manufacturers = all_manufacturers.sort_values(by=customer_data.index[0], ascending=False)
+            # Sort manufacturers by value in descending order and limit to top 20
+            all_manufacturers = all_manufacturers.sort_values(by=customer_data.index[0], ascending=False).head(20)
 
             # Prepare values and manufacturers
             values = all_manufacturers[customer_data.index[0]].values.tolist()
@@ -140,19 +140,13 @@ elif page == "Customer Analysis":
                 else:
                     amounts.append(0)
 
-            # If there are fewer than 3 manufacturers, add a third one with value 0
-            if len(manufacturers) < 3:
-                manufacturers.append("Other")
-                values.append(0)
-                amounts.append(0)
-
             # Display the results for each manufacturer
-            st.write(f"### Results for {len(manufacturers)} manufacturers (sorted):")
+            st.write(f"### Results for top {len(manufacturers)} manufacturers (sorted):")
             for manufacturer, value, amount in zip(manufacturers, values, amounts):
                 st.write(f"{manufacturer} = {value:.4f} units, €{amount:.2f}")
 
             # Create and display the radar chart
-            fig = radar_chart(manufacturers, values, amounts, f'Radar Chart for {len(manufacturers)} Manufacturers of Customer {customer_code}')
+            fig = radar_chart(manufacturers, values, amounts, f'Radar Chart for Top {len(manufacturers)} Manufacturers of Customer {customer_code}')
             st.pyplot(fig)
 
             # Customer sales 2021-2024 (if data exists)