Pre process training data

preprocess.py

   #Prepare event matrix
    input_products = sorted(PRODUCTS[PRODUCTS !='Product A'])
    event_matrix=generate_event_matrix_index(processed_data,input_products)
    x_train_temp=x_train.apply(lambda x : pd.Series(util.encode_events(event_matrix,x[input_products].dropna().items())) ,axis=1)
    x_train=x_train_temp.join(x_train[['cus_type','cus_point']])

    #Preprocess categorial data
    cus_type = CategoricalDtype(categories=processed_data['cus_type'].unique(), ordered=True)
    x_train['cus_type']=x_train['cus_type'].astype(cus_type)
    x_train=pd.get_dummies(x_train,prefix='cus')
    
    #Preprocess continuous data
    cus_point_scaler = MinMaxScaler()
    x_train["cus_point"]=cus_point_scaler.fit_transform(x_train[["cus_point"]])