如何从 groupby 列创建新列并对 pandas 中的另一列进行条件检查？答案

【问题标题】：How to create new column from groupby column and conditional check on another column in pandas?如何从 groupby 列创建新列并对 pandas 中的另一列进行条件检查？
【发布时间】：2020-01-17 14:08:37
【问题描述】：

我有一个熊猫数据框，

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'])

我需要按类型列分组并找到每种类型的最小日期，并为最小日期创建一个新列作为“第一个”，否则为“稍后”

我可以根据类型data.groupby('Type')，我不知道如何在groupdyDF中找到min(data['Date'])并创建一个新列。

我的最终数据看起来像

['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']

【问题讨论】：

标签： python pandas

【解决方案1】：

IIUC 你可以用这个：

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

【讨论】：

【解决方案2】：

IICU，你可以使用np.where 来获取你的输出

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

输出

    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

【讨论】：