python - 如何使用pandas groupby向每个组添加一行？

Question

我希望在每个组的第一行中添加一个新行，我的原始数据框是:

df = pd.DataFrame({
    'ID': ['James', 'James', 'James','Max', 'Max', 'Max', 'Max','Park','Tom', 'Tom', 'Tom', 'Tom','Wong'],
    'From_num': [78, 420, 'Started', 298, 36, 298, 'Started', 'Started', 60, 520, 99, 'Started', 'Started'],
    'To_num': [96, 78, 420, 36, 78, 36, 298, 311, 150, 520, 78, 99, 39],
    'Date': ['2020-05-12', '2020-02-02', '2019-06-18',
             '2019-06-20', '2019-01-30', '2018-10-23',
             '2018-08-29', '2020-05-21', '2019-11-22',
             '2019-08-26', '2018-12-11', '2018-10-09', '2019-02-01']})

是这样的:

      ID From_num  To_num        Date
0   James       78      96  2020-05-12
1   James      420      78  2020-02-02
2   James  Started     420  2019-06-18
3     Max      298      36  2019-06-20
4     Max       36      78  2019-01-30
5     Max      298      36  2018-10-23
6     Max  Started     298  2018-08-29
7    Park  Started     311  2020-05-21
8     Tom       60     150  2019-11-22
9     Tom      520     520  2019-08-26
10    Tom       99      78  2018-12-11
11    Tom  Started      99  2018-10-09
12   Wong  Started      39  2019-02-01

对于每个人(“ID”)，我希望在每个组(“ID”)的第一行上创建一个新的重复行，列“ID”、“From_num”和“To_num”中创建的行的值应该与前第一行相同，但“日期”值是旧的第一行的日期加上一天，例如对于 James，新创建的行值为:'James' '78' '96' '2020-05-13'，与其余数据相同，所以我的预期结果是:

       ID From_num  To_num        Date
0   James       78      96  2020-05-13  # row added, Date + 1
1   James       78      96  2020-05-12
2   James      420      78  2020-02-02
3   James  Started     420  2019-06-18
4     Max      298      36  2019-06-21  # row added, Date + 1
5     Max      298      36  2019-06-20
6     Max       36      78  2019-01-30
7     Max      298      36  2018-10-23
8     Max  Started     298  2018-08-29
9    Park  Started     311  2020-05-22  # Row added, Date + 1
10   Park  Started     311  2020-05-21
11    Tom       60     150  2019-11-23  # Row added, Date + 1
12    Tom       60     150  2019-11-22
13    Tom      520     520  2019-08-26
14    Tom       99      78  2018-12-11
15    Tom  Started      99  2018-10-09
16   Wong  Started      39  2019-02-02  # Row added Date + 1
17   Wong  Started      39  2019-02-01

我写了一些循环条件但是很慢，如果你有什么好的想法，请帮忙。非常感谢

Answer 1

让我们试试 groupby.apply这里。我们将在开始时为每个组添加一行，如下所示:

def augment_group(group):
    first_row = group.iloc[[0]]
    first_row['Date'] += pd.Timedelta(days=1) 
    return first_row.append(group)

df['Date'] = pd.to_datetime(df['Date'], errors='coerce')
(df.groupby('ID', as_index=False, group_keys=False)
   .apply(augment_group)
   .reset_index(drop=True))

       ID From_num  To_num       Date
0   James       78      96 2020-05-13
1   James       78      96 2020-05-12
2   James      420      78 2020-02-02
3   James  Started     420 2019-06-18
4     Max      298      36 2019-06-21
5     Max      298      36 2019-06-20
6     Max       36      78 2019-01-30
7     Max      298      36 2018-10-23
8     Max  Started     298 2018-08-29
9    Park  Started     311 2020-05-22
10   Park  Started     311 2020-05-21
11    Tom       60     150 2019-11-23
12    Tom       60     150 2019-11-22
13    Tom      520     520 2019-08-26
14    Tom       99      78 2018-12-11
15    Tom  Started      99 2018-10-09
16   Wong  Started      39 2019-02-02
17   Wong  Started      39 2019-02-01

尽管我在评论中同意 @Joran Beasley 的观点，认为这有点像 XY 问题。也许尝试澄清您要解决的问题，而不是询问如何实现您认为解决问题的方法？