feat: updated website

app.py

@@ -88,6 +88,7 @@ fieles_df = pd.read_csv("clientes_relevantes.csv")
 cestas = pd.read_csv("cestas.csv")
 productos = pd.read_csv("productos.csv")
 df_agg_2024['cliente_id'] = df_agg_2024['cliente_id'].astype(str)
+marca_id_mapping = load('path_to_file/marca_id_mapping.joblib')
 
 # Convert all columns except 'CLIENTE' to float in euros_proveedor
 for col in euros_proveedor.columns:
@@ -107,6 +108,19 @@ def get_supplier_name(code):
     name = nombres_proveedores[nombres_proveedores['codigo'] == code]['nombre'].values
     return name[0] if len(name) > 0 else code
 
+def get_supplier_name_encoded(encoded_code): 
+    encoded_code = str(encoded_code)  # Ensure the encoded code is a string
+    
+    # First, use the label encoder to get the original manufacturer code
+    if encoded_code in marca_id_mapping.classes_:
+        real_code = marca_id_mapping.inverse_transform([encoded_code])[0]
+    else:
+        return f"Unknown code: {encoded_code}"  # Handle case where encoded code is not found
+    
+    # Now, use the real_code to find the manufacturer name in nombres_proveedores
+    name = nombres_proveedores[nombres_proveedores['codigo'] == real_code]['nombre'].values
+    return name[0] if len(name) > 0 else real_code  # Return real_code if name not found
+
 # Custom Donut Chart with Plotly for Inbound/Outbound Percentage
 def create_donut_chart(values, labels, color_scheme, title):
     fig = px.pie(
@@ -345,7 +359,7 @@ elif page == "Customer Analysis":
                             top_overperformers = overperforming_manufacturers.head(10)
 
                             for index, row in top_overperformers.iterrows():
-                                manufacturer_name = get_supplier_name(row['marca_id_encoded'])
+                                manufacturer_name = get_supplier_name_encoded(row['marca_id_encoded'])
                                 predicted = row['ventas_predichas']
                                 actual = row['ventas_reales']
                                 extra = row['extra_amount']
@@ -422,7 +436,7 @@ elif page == "Customer Analysis":
                             top_misses = underperforming_manufacturers.head(10)
 
                             for index, row in top_misses.iterrows():
-                                manufacturer_name = get_supplier_name(row['marca_id_encoded'])
+                                manufacturer_name = get_supplier_name_encoded(row['marca_id_encoded'])
                                 predicted = row['ventas_predichas']
                                 actual = row['ventas_reales']
                                 missed = row['missed_amount']