Fix app

app.py

@@ -133,19 +133,19 @@ def train_test(dataframe):
   future_X = dataframe.iloc[0:,1:]
   return (training_y, test_y, test_y_series, training_X, test_X, future_X)
 
-@st.cache_data
-def model_fitting(dataframe, Exo):
-    futureModel = pm.auto_arima(dataframe['Sales'], X=Exo, start_p=1, start_q=1,
-                         test='adf',min_p=1,min_q=1,
-                         max_p=3, max_q=3, m=12,
-                         start_P=0, seasonal=True,
-                         d=None, D=1, trace=True,
-                         error_action='ignore',
-                         suppress_warnings=True,
-                         stepwise=True,
-                         maxiter=5)
-    model = futureModel
-    return model
+# @st.cache_data
+# def model_fitting(dataframe, Exo):
+#     futureModel = pm.auto_arima(dataframe['Sales'], X=Exo, start_p=1, start_q=1,
+#                          test='adf',min_p=1,min_q=1,
+#                          max_p=3, max_q=3, m=12,
+#                          start_P=0, seasonal=True,
+#                          d=None, D=1, trace=True,
+#                          error_action='ignore',
+#                          suppress_warnings=True,
+#                          stepwise=True,
+#                          maxiter=5)
+#     model = futureModel
+#     return model
 
 @st.cache_data
 def test_fitting(dataframe, Exo, trainY):
@@ -242,8 +242,8 @@ st.subheader("Welcome User, start using the application by uploading your file i
 if 'uploaded' not in st.session_state:
     st.session_state.uploaded = False
 
-# if 'preprocessed_data' not in st.session_state:
-#     st.session_state.preprocessed_data = None
+if 'forecasted' not in st.session_state:
+    st.session_state.forecasted = False
 
 # Sidebar Menu
 with st.sidebar:
@@ -271,7 +271,7 @@ with st.sidebar:
        st.download_button("Download our sample CSV", f, file_name='sample.csv')
 
 if (st.session_state.uploaded):
-  st.line_chart(series) 
+  st.line_chart(series)
   
   MIN_DAYS = 30
   MAX_DAYS = 90
@@ -284,7 +284,7 @@ if (st.session_state.uploaded):
     type="primary",
   )
 
-  if (forecast_button):
+  if (forecast_button or st.session_state.forecasted):
     df = series_to_df_exogenous(series)
 
     train = train_test(df)
@@ -292,6 +292,7 @@ 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
 
     fitted, confint = train_test_model.predict(X=test_X, n_periods=n_periods, return_conf_int=True)
@@ -316,10 +317,11 @@ 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)
     st.write("Forecasted sales in the next 3 months")
     st.write(df)
+    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?")