Version 1 hotfix #31 for merge

app.py

@@ -343,36 +343,35 @@ if (st.session_state.uploaded):
     test_y, predictions = np.array(test_y), np.array(fitted)
     score = forecast_accuracy(predictions, test_y)
     mape, interpretation = interpret_mape(score['mape'])
+    
+    merged_data = merge_forecast_data(df['Sales'], fitted_series, future_fitted_series)
+    
+    fig = go.Figure()
+    fig.add_trace(go.Scatter(x=merged_data[merged_data.columns[0]], y=merged_data['Actual Sales'], mode='lines', name='Actual Sales'))
+    fig.add_trace(go.Scatter(x=merged_data[merged_data.columns[0]], y=merged_data['Predicted Sales'], mode='lines', name='Predicted Sales'))
+    fig.add_trace(go.Scatter(x=merged_data[merged_data.columns[0]], y=merged_data['Forecasted Future Sales'], mode='lines', name='Forecasted Future Sales'))
+    fig.update_layout(title='Forecasted Sales Data', xaxis_title='Date', yaxis_title='Sales')
+    fig.update_xaxes(range=['2020-01-01', '2025-01-01']) # TODO: Change this to be adaptive
+    st.plotly_chart(fig)
+    st.write(f"MAPE score: {mape}% - {interpretation}")
 
     col = st.columns(2)
     with col[0]:
-      merged_data = merge_forecast_data(df['Sales'], fitted_series, future_fitted_series)
-      
-      fig = go.Figure()
-      fig.add_trace(go.Scatter(x=merged_data[merged_data.columns[0]], y=df['Sales'], mode='lines', name='Actual Sales'))
-      fig.add_trace(go.Scatter(x=merged_data[merged_data.columns[0]], y=merged_data['Predicted Sales'], mode='lines', name='Predicted Sales'))
-      fig.add_trace(go.Scatter(x=merged_data[merged_data.columns[0]], y=merged_data['Forecasted Future Sales'], mode='lines', name='Forecasted Future Sales'))
-      fig.update_layout(title='Forecasted Sales Data', xaxis_title='Date', yaxis_title='Sales')
-      fig.update_xaxes(range=['2020-01-01', '2025-01-01']) # TODO: Change this to be adaptive
-      col[0].plotly_chart(fig)
-      col[0].write(f"MAPE score: {mape}% - {interpretation}")
+      col[0].subheader(f"Forecasted sales in the next {period} days")
+      col[0].write(df)
     with col[1]:
-      col[1].subheader(f"Forecasted sales in the next {period} days")
-      col[1].write(df)
+      with st.form("question_form"):
+        question = col[1].text_input('Ask a Question about the Forecasted Data', placeholder="What is the total sales in the month of December?")
+        query_button = col[1].form_submit_button(label='Generate Answer')
+      if query_button or question:
+          answer = get_converted_answer(df, question)
+          if answer is not None:
+            col[1].subheader("The answer is:", answer)
+          else:
+            col[1].subheader("Answer is not found in table")
     st.session_state.forecasted = True
 
 
-    with st.form("question_form"):
-        question = st.text_input('Ask a Question about the Forecasted Data', placeholder="What is the total sales in the month of December?")
-        query_button = st.form_submit_button(label='Generate Answer')
-
-    if query_button or question:
-        answer = get_converted_answer(df, question)
-        if answer is not None:
-          st.subheader("The answer is:", answer)
-        else:
-           st.subheader("Answer is not found in table")
-
 # Hide Streamlit default style
 hide_st_style = """
             <style>