feat: generated files

app.py

@@ -10,8 +10,10 @@ st.set_page_config(page_title="Customer Insights App", page_icon=":bar_chart:")
 # Load CSV files
 df = pd.read_csv("df_clean.csv")
 nombres_proveedores = pd.read_csv("nombres_proveedores.csv", sep=';')
+euros_proveedor = pd.read_csv("euros_proveedor.csv", sep=',')
 
 nombres_proveedores['codigo'] = nombres_proveedores['codigo'].astype(str)
+euros_proveedor['CLIENTE'] = euros_proveedor['CLIENTE'].astype(str)
 
 # Ignore the last two columns
 df = df.iloc[:, :-2]
@@ -25,7 +27,7 @@ def get_supplier_name(code):
     return name[0] if len(name) > 0 else code
 
 # Function to create radar chart
-def radar_chart(categories, values, title):
+def radar_chart(categories, values, amounts, title):
     # Number of variables
     N = len(categories)
     
@@ -36,18 +38,29 @@ def radar_chart(categories, values, title):
     # Initialize the plot
     fig, ax = plt.subplots(figsize=(12, 12), subplot_kw=dict(projection='polar'))
     
-    # Draw polygon and fill it
-    values += values[:1]
-    ax.plot(angles, values, 'o-', linewidth=2, color='#FF69B4')
-    ax.fill(angles, values, alpha=0.25, color='#FF69B4')
+    # Normalize values and amounts
+    max_value = max(values)
+    normalized_values = [v / max_value for v in values]
+    total_amount = sum(amounts)
+    normalized_amounts = [a / total_amount for a in amounts]
+    
+    # Draw polygon for units and fill it
+    normalized_values += normalized_values[:1]
+    ax.plot(angles, normalized_values, 'o-', linewidth=2, color='#FF69B4', label='% Units')
+    ax.fill(angles, normalized_values, alpha=0.25, color='#FF69B4')
+    
+    # Draw polygon for amounts and fill it
+    normalized_amounts += normalized_amounts[:1]
+    ax.plot(angles, normalized_amounts, 'o-', linewidth=2, color='#4B0082', label='% Spend')
+    ax.fill(angles, normalized_amounts, alpha=0.25, color='#4B0082')
     
     # Set axes
     ax.set_xticks(angles[:-1])
     ax.set_xticklabels(categories, size=8, wrap=True)
-    ax.set_ylim(0, max(values) * 1.1)
+    ax.set_ylim(0, max(max(normalized_values), max(normalized_amounts)) * 1.1)
     
     # Draw reference circles
-    circles = np.linspace(0, max(values), 5)
+    circles = np.linspace(0, 1, 5)
     for circle in circles:
         ax.plot(angles, [circle]*len(angles), '--', color='gray', alpha=0.3, linewidth=0.5)
     
@@ -55,8 +68,9 @@ def radar_chart(categories, values, title):
     ax.set_yticklabels([])
     ax.spines['polar'].set_visible(False)
     
-    # Add title
+    # Add title and legend
     plt.title(title, size=16, y=1.1)
+    plt.legend(loc='upper right', bbox_to_anchor=(1.3, 1.1))
     
     return fig
 
@@ -100,8 +114,9 @@ elif page == "Customer Analysis":
     if customer_code:
         # Filter data for the selected customer
         customer_data = df[df["CLIENTE"] == customer_code]
+        customer_euros = euros_proveedor[euros_proveedor["CLIENTE"] == customer_code]
 
-        if not customer_data.empty:
+        if not customer_data.empty and not customer_euros.empty:
             st.write(f"### Analysis for Customer {customer_code}")
 
             # Define purchase threshold
@@ -117,18 +132,27 @@ elif page == "Customer Analysis":
             values = all_manufacturers[customer_data.index[0]].values.tolist()
             manufacturers = [get_supplier_name(m) for m in all_manufacturers.index.tolist()]
 
+            # Get amounts in euros
+            amounts = []
+            for m in all_manufacturers.index.tolist():
+                if m in customer_euros.columns:
+                    amounts.append(customer_euros[m].values[0])
+                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):")
-            for manufacturer, value in zip(manufacturers, values):
-                st.write(f"{manufacturer} = {value:.4f}")
+            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, f'Radar Chart for {len(manufacturers)} Manufacturers of Customer {customer_code}')
+            fig = radar_chart(manufacturers, values, amounts, f'Radar Chart for {len(manufacturers)} Manufacturers of Customer {customer_code}')
             st.pyplot(fig)
 
             # Customer sales 2021-2024 (if data exists)