Version 1 hotfix #22 for merge

app.py

@@ -7,7 +7,7 @@ import numpy as np
 import pmdarima as pm
 import matplotlib.pyplot as plt
 from pmdarima import auto_arima
-# import plotly.graph_objects as go
+import plotly.graph_objects as go
 
 import torch
 from transformers import pipeline, TapasTokenizer, TapasForQuestionAnswering
@@ -371,11 +371,14 @@ if (st.session_state.uploaded):
     col = st.columns(2)
     with col[0]:
       col[0].header("Sales Forecast")
-      #  merged_data = plot_data(df['Sales'], fitted_series, future_fitted_series)
-      # date = get_combined_date(df['Sales'], fitted_series, future_fitted_series)
-      # col[0].line_chart(x=date, y=[df['Sales'], fitted_series], color='blue', key='actual')
       merged_data = merge_forecast_data(df['Sales'], fitted_series, future_fitted_series)
-      col[0].line_chart(merged_data, x="index", y=["Actual Sales", "Predicted Sales", "Future Forecasted Sales"])
+      
+      fig = go.Figure()
+      fig.add_trace(go.Scatter(x=merged_data['Date'], y=merged_data['Sales_Actual'], mode='lines', name='Actual Sales'))
+      fig.add_trace(go.Scatter(x=merged_data['Date'], y=merged_data['Sales_Predicted'], mode='lines', name='Predicted Sales'))
+      fig.add_trace(go.Scatter(x=merged_data['Date'], y=merged_data['Sales_Forecasted'], mode='lines', name='Forecasted Sales'))
+      fig.update_layout(title='Forecasted Sales Data', xaxis_title='Date', yaxis_title='Sales')
+      col[0].plotly_chart(fig)
       col[0].write(f"MAPE score: {acc['mape']} (lower is better)")
     with col[1]:
       col[1].subheader(f"Forecasted sales in the next {period} days")