CODEWITHSUNDEEP
pandas
Jack
Jack

Reputation: 1754

get the start date of the week for pandas DatetimeIndex?

date_idx 

DatetimeIndex(['2021-05-14', '2021-05-17', '2021-05-18', '2021-05-19',
               '2021-05-20', '2021-05-21', '2021-05-24', '2021-05-25',
               '2021-05-26', '2021-05-27', '2021-05-28', '2021-05-31',
               '2021-06-01', '2021-06-02', '2021-06-03', '2021-06-04',
               '2021-06-07', '2021-06-08', '2021-06-09', '2021-06-10',
               '2021-06-11', '2021-06-15', '2021-06-16', '2021-06-17',
               '2021-06-18', '2021-06-21', '2021-06-22', '2021-06-23',
               '2021-06-24', '2021-06-25', '2021-06-28', '2021-06-29',
               '2021-06-30', '2021-07-01', '2021-07-02', '2021-07-05',
               '2021-07-06', '2021-07-07', '2021-07-08', '2021-07-09',
               '2021-07-12', '2021-07-13', '2021-07-14', '2021-07-15',
               '2021-07-16', '2021-07-19', '2021-07-20', '2021-07-21',
               '2021-07-22', '2021-07-23'],
              dtype='datetime64[ns]', name='date', freq=None)

Goal

Try

date_idx- date_idx.weekday * np.timedelta64(1, 'D')

Upvotes: 0

Views: 57

Answers (1)

Henry Yik
Henry Yik

Reputation: 22493

IIUC you can groupby with freq="W" and then transform first:

date_idx.to_frame(False).groupby(pd.Grouper(freq="W", key="date"))["date"].transform("first")

0    2021-05-14
1    2021-05-17
2    2021-05-17
3    2021-05-17
4    2021-05-17
5    2021-05-17
6    2021-05-24
7    2021-05-24
8    2021-05-24
9    2021-05-24
10   2021-05-24
11   2021-05-31
12   2021-05-31
13   2021-05-31
14   2021-05-31
15   2021-05-31
16   2021-06-07
17   2021-06-07
18   2021-06-07
19   2021-06-07
20   2021-06-07
21   2021-06-15
22   2021-06-15
23   2021-06-15
24   2021-06-15
25   2021-06-21
26   2021-06-21
27   2021-06-21
28   2021-06-21
29   2021-06-21
30   2021-06-28
31   2021-06-28
32   2021-06-28
33   2021-06-28
34   2021-06-28
35   2021-07-05
36   2021-07-05
37   2021-07-05
38   2021-07-05
39   2021-07-05
40   2021-07-12
41   2021-07-12
42   2021-07-12
43   2021-07-12
44   2021-07-12
45   2021-07-19
46   2021-07-19
47   2021-07-19
48   2021-07-19
49   2021-07-19
Name: date, dtype: datetime64[ns]

Upvotes: 1

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