Update app showing graphs

app.py

@@ -315,9 +315,8 @@ if (st.session_state.uploaded):
     train_test_model = test_fitting(df, training_X, training_y)
     
     n_periods = round(len(df) * 0.2)
-    future_n_periods = forecast_period + n_periods
+    future_n_periods = forecast_period
     fitted, confint = train_test_model.predict(X=test_X, n_periods=n_periods, return_conf_int=True)
-    index_of_fc = test_y_series.index
 
     # make series for plotting purpose
     fitted_series = pd.Series(fitted)
@@ -337,7 +336,6 @@ if (st.session_state.uploaded):
     future_upper_series = pd.Series(confint[:, 1], index=future_index_of_fc)
 
     future_sales_growth = sales_growth(df, future_fitted_series)
-    future_sales_growth = future_sales_growth.iloc[n_periods:]
     df = dates_df(future_sales_growth)
 
     test_y, predictions = np.array(test_y), np.array(fitted)
@@ -346,21 +344,29 @@ if (st.session_state.uploaded):
     
     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, use_container_width=True)
-    st.write(f"MAPE score: {mape}% - {interpretation}")
-
-    col = st.columns(2)
-    with col[0]:
-      col[0].subheader(f"Forecasted sales in the next {period} days")
-      col[0].write(df)
-    with col[1]:
-      col[1] = st.subheader("Question-Answering")
+
+    col_charts = st.columns(2)
+      with col_charts[0]:
+        fig_compare = go.Figure()
+        fig_compare.add_trace(go.Scatter(x=merged_data[merged_data.columns[0]], y=merged_data['Actual Sales'], mode='lines', name='Actual Sales'))
+        fig_compare.add_trace(go.Scatter(x=merged_data[merged_data.columns[0]], y=merged_data['Predicted Sales'], mode='lines', name='Predicted Sales'))
+        fig_compare.update_layout(title='Historical Sales Data', xaxis_title='Date', yaxis_title='Sales')
+        fig_compare.update_xaxes(range=['2020-01-01', '2025-01-01']) # TODO: Change this to be adaptive
+        st.plotly_chart(fig_compare, use_container_width=True)
+      with col_charts[1]:
+        fig_forecast = go.Figure()
+        fig_compare.add_trace(go.Scatter(x=merged_data[merged_data.columns[0]], y=merged_data['Forecasted Future Sales'], mode='lines', name='Forecasted Future Sales'))
+        fig_compare.update_layout(title='Forecasted Sales Data', xaxis_title='Date', yaxis_title='Sales')
+        # fig_compare.update_xaxes(range=['2020-01-01', '2025-01-01']) # TODO: Change this to be adaptive
+        st.plotly_chart(fig_compare, use_container_width=True)
+        st.write(f"MAPE score: {mape}% - {interpretation}")
+
+    col_table = st.columns(2)
+    with col_table[0]:
+      col_table[0].subheader(f"Forecasted sales in the next {period} days")
+      col_table[0].write(df)
+    with col_table[1]:
+      col_table[1] = st.subheader("Question-Answering")
       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')