Update src/streamlit_app.py

src/streamlit_app.py

@@ -272,4 +272,94 @@ if forecast is not None:
     # Metrics
     mae = mean_absolute_error(test, forecast)
     mse = mean_squared_error(test, forecast)
-    rm
+    rmse = np.sqrt(mse)
+    
+    st.subheader("📈 Forecast Results")
+    col1, col2, col3 = st.columns(3)
+    col1.metric("MAE", f"{mae:.2f}")
+    col2.metric("MSE", f"{mse:.2f}")
+    col3.metric("RMSE", f"{rmse:.2f}")
+
+    # Plot forecast vs actual
+    fig = go.Figure()
+    fig.add_trace(go.Scatter(x=train.index, y=train, mode='lines', name='Training', line=dict(color='blue')))
+    fig.add_trace(go.Scatter(x=test.index, y=test, mode='lines', name='Actual', line=dict(color='green')))
+    fig.add_trace(go.Scatter(x=test.index, y=forecast, mode='lines+markers', name='Forecast', line=dict(color='red', dash='dash')))
+    fig.update_layout(
+        title=f"{model_choice} Forecast",
+        xaxis_title="Date",
+        yaxis_title=value_col,
+        legend=dict(x=0, y=1)
+    )
+    st.plotly_chart(fig, use_container_width=True)
+
+    # Allow forecasting into future
+    st.subheader("🔮 Forecast Future Periods")
+    future_periods = st.number_input("Number of future periods to forecast:", min_value=1, max_value=365, value=30, step=1)
+    
+    if st.button("🚀 Generate Future Forecast"):
+        try:
+            if model_choice == "Holt-Winters Exponential Smoothing":
+                future_forecast = model.forecast(future_periods)
+                last_date = ts.index[-1]
+                if freq == 'D':
+                    future_dates = pd.date_range(start=last_date + pd.Timedelta(days=1), periods=future_periods, freq='D')
+                elif freq == 'W':
+                    future_dates = pd.date_range(start=last_date + pd.Timedelta(weeks=1), periods=future_periods, freq='W')
+                elif freq == 'M':
+                    future_dates = pd.date_range(start=last_date + pd.DateOffset(months=1), periods=future_periods, freq='M')
+                else:
+                    future_dates = pd.date_range(start=last_date + pd.Timedelta(days=1), periods=future_periods, freq='D')
+                
+            elif model_choice == "ARIMA":
+                future_forecast = model.forecast(future_periods)
+                last_date = ts.index[-1]
+                if freq == 'D':
+                    future_dates = pd.date_range(start=last_date + pd.Timedelta(days=1), periods=future_periods, freq='D')
+                elif freq == 'W':
+                    future_dates = pd.date_range(start=last_date + pd.Timedelta(weeks=1), periods=future_periods, freq='W')
+                elif freq == 'M':
+                    future_dates = pd.date_range(start=last_date + pd.DateOffset(months=1), periods=future_periods, freq='M')
+                else:
+                    future_dates = pd.date_range(start=last_date + pd.Timedelta(days=1), periods=future_periods, freq='D')
+                
+            elif model_choice == "Prophet":
+                last_date = ts.index[-1]
+                if freq == 'D':
+                    future_dates = pd.date_range(start=last_date + pd.Timedelta(days=1), periods=future_periods, freq='D')
+                elif freq == 'W':
+                    future_dates = pd.date_range(start=last_date + pd.Timedelta(weeks=1), periods=future_periods, freq='W')
+                elif freq == 'M':
+                    future_dates = pd.date_range(start=last_date + pd.DateOffset(months=1), periods=future_periods, freq='M')
+                else:
+                    future_dates = pd.date_range(start=last_date + pd.Timedelta(days=1), periods=future_periods, freq='D')
+                
+                future_df = pd.DataFrame({'ds': future_dates})
+                forecast_df = model.predict(future_df)
+                future_forecast = forecast_df['yhat'].values
+
+            # Plot future forecast
+            fig_future = go.Figure()
+            fig_future.add_trace(go.Scatter(x=ts.index, y=ts.values, mode='lines', name='Historical', line=dict(color='blue')))
+            fig_future.add_trace(go.Scatter(x=future_dates, y=future_forecast, mode='lines+markers', name='Future Forecast', line=dict(color='red', dash='dash')))
+            fig_future.update_layout(
+                title="Future Forecast",
+                xaxis_title="Date",
+                yaxis_title=value_col
+            )
+            st.plotly_chart(fig_future, use_container_width=True)
+
+            # Show as table
+            forecast_df = pd.DataFrame({
+                'Date': future_dates,
+                'Forecast': future_forecast
+            })
+            with st.expander("📋 View Forecast Table"):
+                st.dataframe(forecast_df)
+
+        except Exception as e:
+            st.error(f"Could not generate future forecast: {e}")
+
+# Footer
+st.markdown("---")
+st.caption(f"© {AUTHOR} | License {LICENSE} | Contact: {EMAIL}")