最初の注文日と顧客一人当たりの金額を返します

Question

私は、列としてinitial_order_DTを返し、別の列としてinitial_order_valueを返すPython（pandas）スクリプトを実行しようとしています。

入力：

 Order ID  Customer ID Value Date 
     00000001  0001   1500  10/01/2017 
     00000002  0001   1300  11/15/2017 
     00000003  0001   1200  12/12/2017 
     00000004  0002   500  12/13/2017 
     00000005  0003   1750  09/15/2017 
     00000006  0003   1800  10/01/2017 
     00000007  0003   1600  11/01/2017 
     00000008  0003   1400  12/01/2017 

出力：

 Order ID  Customer ID Value Date First_Order_DT First_Value 
     00000001  0001   1500 //  10/01/2017 1500 
     00000002  0001   1300 //  10/01/2017 1500 
     00000003  0001   1200 //  10/01/2017 1500 
     00000004  0002   500  //  12/13/2017 500 
     00000005  0003   1750 //  09/15/2017 1750 
     00000006  0003   1800 //  09/15/2017 1750 
     00000007  0003   1600 //  09/15/2017 1750 
     00000008  0003   1400  etc 09/15/2017 1750 

Answer 1

あなたはgroupby + transformでこれを行うことができます -

v = df.groupby('Customer ID')['Date', 'Value'].transform('first').add_prefix('First_') 
v 
    First_Date First_Value 
0 10/01/2017   1500 
1 10/01/2017   1500 
2 10/01/2017   1500 
3 12/13/2017   500 
4 09/15/2017   1750 
5 09/15/2017   1750 
6 09/15/2017   1750 
7 09/15/2017   1750 

を連結vオリジナルとdf -

df = pd.concat([df, v], 1) 
df 

    Order ID Customer ID Value  Date First_Date First_Value 
0   1   1 1500 10/01/2017 10/01/2017   1500 
1   2   1 1300 11/15/2017 10/01/2017   1500 
2   3   1 1200 12/12/2017 10/01/2017   1500 
3   4   2 500 12/13/2017 12/13/2017   500 
4   5   3 1750 09/15/2017 09/15/2017   1750 
5   6   3 1800 10/01/2017 09/15/2017   1750 
6   7   3 1600 11/01/2017 09/15/2017   1750 
7   8   3 1400 12/01/2017 09/15/2017   1750