Update app.py

app.py

@@ -125,16 +125,16 @@ def create_test_plot(train_data, test_data, predicted_data, company_name):
     fig = go.Figure()
 
     fig.add_trace(go.Scatter(
-        x=train_data.index,
-        y=train_data['Close'],
+        x=train_data['ds'],
+        y=train_data['y'],
         mode='lines',
         name='Training Data',
         line=dict(color='blue')
     ))
 
     fig.add_trace(go.Scatter(
-        x=test_data.index,
-        y=test_data['Close'],
+        x=test_data['ds'],
+        y=test_data['y'],
         mode='lines',
         name='Actual (Test) Data',
         line=dict(color='green')
@@ -142,7 +142,7 @@ def create_test_plot(train_data, test_data, predicted_data, company_name):
 
     if predicted_data is not None:
         fig.add_trace(go.Scatter(
-            x=test_data.index,  # Align predicted data with test data
+            x=test_data['ds'],  # Align predicted data with test data
             y=predicted_data['yhat'][-len(test_data):],
             mode='lines',
             name='Predicted Data',
@@ -288,7 +288,7 @@ def test_model():
                             st.metric("Mean Squared Error", f"{mse:.4f}")
                             st.metric("Root Mean Squared Error", f"{rmse:.4f}")
 
-                            plot = create_test_plot(predictor.data, test_data, test_pred, company_name)
+                            plot = create_test_plot(predictor.data, test_data.reset_index().rename(columns={'Date': 'ds', 'Close': 'y'}), test_pred, company_name)
                             st.plotly_chart(plot, use_container_width=True)
                         else:
                             st.error("Failed to evaluate the model. The evaluation metrics are None.")