Version 1 hotfix #26 for merge

app.py

@@ -176,7 +176,6 @@ def sales_growth(dataframe, fittedValues):
     sales_growth['Forecasted Sales First Difference'].iloc[0] = (dataframe['Sales'].iloc[-1]-dataframe['Sales'].iloc[-2]).round(2)
     sales_growth['Forecasted Sales Growth'].iloc[0]=(((dataframe['Sales'].iloc[-1]-dataframe['Sales'].iloc[-2])/dataframe['Sales'].iloc[-1])*100).round(2)
 
-
     return sales_growth
 
 @st.cache_data
@@ -196,24 +195,16 @@ def merge_forecast_data(actual, predicted, future):
     return merged_dataframe
 
 @st.cache_data
-def get_combined_date(actual, predicted, future):
-  actual = actual.to_frame()
-  predicted = predicted.to_frame()
-  future = future.to_frame()
-  future = future.rename_axis('Date')
-
-  actual = actual.reset_index()
-  predicted = predicted.reset_index()
-  future = future.reset_index()
-
-  actual_date = actual['Date'].to_frame()
-  predicted_date = predicted['Date'].to_frame()
-  future_date = future['Date'].to_frame()
-
-  combined_date = pd.concat([actual_date, predicted_date, future_date])
-  combined_date = combined_date.reset_index()
-  combined_date = combined_date.drop(columns='index')
-  return combined_date
+def interpret_mape(acc):
+  acc = acc * 100
+  if acc['mape'] < 10:
+    return "Great"
+  elif acc['mape'] < 20:
+    return "Good"
+  elif acc['mape'] < 50:
+    return "Relatively Good"
+  else:
+    return "Poor"
 
 # TAPAS Model
 
@@ -366,10 +357,10 @@ if (st.session_state.uploaded):
 
     test_y, predictions = np.array(test_y), np.array(fitted)
     acc = forecast_accuracy(predictions, test_y)
+    interpretation = interpret_mape(acc)
 
     col = st.columns(2)
     with col[0]:
-      col[0].header("Sales Forecast")
       merged_data = merge_forecast_data(df['Sales'], fitted_series, future_fitted_series)
       
       fig = go.Figure()
@@ -377,8 +368,9 @@ if (st.session_state.uploaded):
       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=['2018-01-01', '2026-01-01'])
       col[0].plotly_chart(fig)
-      col[0].write(f"MAPE score: {acc['mape']} (lower is better)")
+      col[0].write(f"MAPE score: {acc['mape'] * 100}% - {interpretation}")
     with col[1]:
       col[1].subheader(f"Forecasted sales in the next {period} days")
       col[1].write(df)