如何從 groupby 列創建新列並對熊貓中的另一列進行條件檢查？

Question

我有一個熊貓數據框，

data = pd.DataFrame([['TRAN','2019-01-06T21:44:09Z','T'],
                     ['LMI','2019-01-06T19:44:09Z','U'],
                     ['ARN','2019-01-02T19:44:09Z','V'],
                     ['TRAN','2019-01-08T06:44:09Z','T'],
                     ['TRAN','2019-01-06T18:44:09Z','U'],
                     ['ARN','2019-01-04T19:44:09Z','V'],
                     ['LMI','2019-01-05T16:34:09Z','U'],
                     ['ARN','2019-01-08T19:44:09Z','V'],
                     ['TRAN','2019-01-07T14:44:09Z','T'],
                     ['TRAN','2019-01-06T11:44:09Z','U'],
                     ['ARN','2019-01-10T19:44:09Z','V'],
                     ], 
                    columns=['Type', 'Date', 'Decision'])

我需要按類型列分組並找到每種類型的最小日期並為最小日期創建一個新列作為“第一個”否則為“稍后”

我可以基於data.groupby('Type') ，我不知道如何在 groupdyDF 中找到min(data['Date'])並創建一個新列。

我的最終數據看起來像

['TRAN','2019-01-06T21:44:09Z','T','Later'],
['LMI','2019-01-06T19:44:09Z','U','Later'],
['ARN','2019-01-02T19:44:09Z','V','First'],
['TRAN','2019-01-08T06:44:09Z','T','Later'],
['TRAN','2019-01-06T18:44:09Z','U','Later'],
['ARN','2019-01-04T19:44:09Z','V','Later'],
['LMI','2019-01-05T16:34:09Z','U','First'],
['ARN','2019-01-08T19:44:09Z','V','Later'],
['TRAN','2019-01-07T14:44:09Z','T','Later'],
['TRAN','2019-01-06T11:44:09Z','U','First'],
['ARN','2019-01-10T19:44:09Z','V','Later'],
], 
columns=['Type', 'Date', 'Decision']

Answer 1

IIUC你可以使用這個：

df.groupby('Type').agg(First=('Date','first'), Later=('Date','last')).reset_index()

Answer 2

IICU，您可以使用np.where來獲取您的輸出

data['check']=np.where(data.Date > data.groupby('Type')['Date'].transform(min), 'Later','First')
print(data)

輸出

    Type            Date    Decision    check
0   TRAN    2019-01-06T21:44:09Z    T   Later
1   LMI     2019-01-06T19:44:09Z    U   Later
2   ARN     2019-01-02T19:44:09Z    V   First
3   TRAN    2019-01-08T06:44:09Z    T   Later
4   TRAN    2019-01-06T18:44:09Z    U   Later
5   ARN     2019-01-04T19:44:09Z    V   Later
6   LMI     2019-01-05T16:34:09Z    U   First
7   ARN     2019-01-08T19:44:09Z    V   Later
8   TRAN    2019-01-07T14:44:09Z    T   Later
9   TRAN    2019-01-06T11:44:09Z    U   First
10  ARN     2019-01-10T19:44:09Z    V   Later