Update app.py

app.py

@@ -2,6 +2,7 @@ import streamlit as st
 import numpy as np
 import pandas as pd
 import plotly.express as px
+import plotly.graph_objs as go
 from statsforecast import StatsForecast
 from statsforecast.models import seasonal_naive, auto_arima
 from utils import calc_seasonality
@@ -39,16 +40,51 @@ if uploaded_file is not None:
                               )
           forecasts = fcst.forecast(horizons, level=(80, 95))
           st.write(forecasts)
-          fig.add_scatter(x=forecasts['ds'], y=forecasts[f'auto_arima_season_length-{seasonality}_mean'], mode='lines')
-          fig.update_traces(
-                             name=f'auto_arima_season_length-{seasonality}_mean',
-                             line=dict(color='green', width=1),
-                             showlegend=True
-          )
-          fig.add_scatter(x=forecasts['ds'], y=forecasts[f'seasonal_naive_season_length-{seasonality}'], mode='lines')
-          fig.update_traces(
-                             name=f'seasonal_naive_season_length-{seasonality}',
-                             line=dict(color='red', width=1),
-                             showlegend=True
-          )
+          
+          fig_forecast = go.Figure([
+                       go.Scatter(
+                           name=series,
+                           x=series_train['ds'],
+                           y=series_train['y'],
+                           mode='line',
+                           line=dict(color='blue', width=1),
+                           showlegend=True
+                       ),
+                       go.Scatter(
+                           name=f'auto_arima_season_length-{seasonality}_mean',
+                           x=forecasts['ds'],
+                           y=forecasts[f'auto_arima_season_length-{seasonality}_mean'],
+                           mode='lines',
+                           line=dict(color='green', width=1),
+                           showlegend=True
+                       ),
+                       go.Scatter(
+                           name=f'seasonal_naive_season_length-{seasonality}',
+                           x=forecasts['Time'],
+                           y=forecasts[f'seasonal_naive_season_length-{seasonality}'],
+                           line=dict(color='red', width=1),
+                           mode='lines',
+                           fillcolor='rgba(68, 68, 68, 0.3)',
+                           fill='tonexty',
+                           showlegend=True
+                       )
+                   ])
+          fig.update_layout(
+                       yaxis_title=series,
+                       title=f'Forecasting {series}'
+                   )
           st.plotly_chart(fig)
+                             
+#          fig.add_scatter(x=forecasts['ds'], y=forecasts[f'auto_arima_season_length-{seasonality}_mean'], mode='lines')
+#          fig.update_traces(
+#                             name=f'auto_arima_season_length-{seasonality}_mean',
+#                             line=dict(color='green', width=1),
+#                             showlegend=True
+#          )
+#          fig.add_scatter(x=forecasts['ds'], y=forecasts[f'seasonal_naive_season_length-{seasonality}'], mode='lines')
+#          fig.update_traces(
+#                             name=f'seasonal_naive_season_length-{seasonality}',
+#                             line=dict(color='red', width=1),
+#                             showlegend=True
+#          )
+#          st.plotly_chart(fig)