Gyimah3 commited on
Commit
d29f5f3
·
1 Parent(s): f6a49ae

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +4 -3
app.py CHANGED
@@ -73,7 +73,7 @@ elif social_acc_nav == 'About App':
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  st.sidebar.markdown("This App predicts the sales for product families sold at Favorita stores using regression model.")
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  st.sidebar.markdown("")
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  st.sidebar.markdown("[ Visit Github Repository for more information](https://github.com/Kyei-frank/Regression-Project-Store-Sales--Time-Series-Forecasting)")
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- st.sidebar.markdown("For mom❄️ and Delp❄️.")
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  st.sidebar.markdown("")
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@@ -85,7 +85,7 @@ def Load_ml_items(relative_path):
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  loaded_object1 = pickle.load(file)
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  return loaded_object1
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- @st.cache_data(allow_output_mutation=True)
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  def Load_ml_items(relative_path):
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  "Load ML items to reuse them"
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  with open(relative_path, 'rb') as file:
@@ -103,8 +103,9 @@ loaded_object1 = Load_ml_items('ML_items')
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  Loaded_object = Load_ml_items('ml_items_1')
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  pipeline, stores, holidays_event = Loaded_object['pipeline'], Loaded_object['stores'], Loaded_object['holidays_event']
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  train_data= loaded_object1['train_data']
 
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  # Setting Function for extracting Calendar features
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- @st.cache_data(allow_output_mutation=True)
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  def getDateFeatures(df, date ):
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  df['date'] = pd.to_datetime(df[date])
 
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  st.sidebar.markdown("This App predicts the sales for product families sold at Favorita stores using regression model.")
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  st.sidebar.markdown("")
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  st.sidebar.markdown("[ Visit Github Repository for more information](https://github.com/Kyei-frank/Regression-Project-Store-Sales--Time-Series-Forecasting)")
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+ st.sidebar.markdown("For mom❄️ and Dad❄️.")
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  st.sidebar.markdown("")
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  loaded_object1 = pickle.load(file)
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  return loaded_object1
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+ @st.cache_data()
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  def Load_ml_items(relative_path):
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  "Load ML items to reuse them"
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  with open(relative_path, 'rb') as file:
 
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  Loaded_object = Load_ml_items('ml_items_1')
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  pipeline, stores, holidays_event = Loaded_object['pipeline'], Loaded_object['stores'], Loaded_object['holidays_event']
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  train_data= loaded_object1['train_data']
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+
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  # Setting Function for extracting Calendar features
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+ @st.cache_data()
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  def getDateFeatures(df, date ):
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  df['date'] = pd.to_datetime(df[date])