Keras 这是为每位顾客准备的 item_a item_b item_c item_d customer_id visit dates 6/01 1

这是为每位顾客准备的

item_a  item_b  item_c  item_d  customer_id  visit
dates                                             
6/01       1      0      0      0  cust_123      1
6/02       0      0      0      0  cust_123      0
6/03       0      1      0      0  cust_123      1
6/04       0      0      0      0  cust_123      0
6/05       1      0      0      0  cust_123      1
6/06       0      0      0      0  cust_123      0
6/07       0      0      0      0  cust_123      0
6/08       1      0      0      0  cust_123      1
6/01       0      0      0      0  cust_456      0
6/02       0      0      0      0  cust_456      0
6/03       0      0      0      0  cust_456      0
6/04       0      0      0      0  cust_456      0
6/05       1      0      0      0  cust_456      1
6/06       0      0      0      0  cust_456      0
6/07       0      0      0      0  cust_456      0
6/08       0      0      0      0  cust_456      0
6/01       0      0      0      0  cust_789      0
6/02       0      0      0      0  cust_789      0
6/03       0      0      0      0  cust_789      0
6/04       0      0      0      0  cust_789      0
6/05       0      0      0      0  cust_789      0
6/06       0      0      0      0  cust_789      0
6/07       0      0      0      0  cust_789      0
6/08       0      1      1      0  cust_789      1

df['target_variable']='no_purchase'
for cust in list(set(df['customer'])):
  df['target_variable']=np.where(df['visit']>0,cust,df['target_variable'])