pd.Series.dt.strftime
¶
pandas.Series.dt.strftime(date_format)
Supported Arguments¶
argument | datatypes | other requirements |
---|---|---|
date_format |
String | Must be a valid datetime format string |
Example Usage¶
>>> @bodo.jit
... def f(S):
... return S.dt.strftime("%B %d, %Y, %r")
>>> S = pd.Series(pd.date_range(start='1/1/2022', end='1/10/2022', periods=30))
>>> f(S)
0 January 01, 2022, 12:00:00 AM
1 January 01, 2022, 07:26:53 AM
2 January 01, 2022, 02:53:47 PM
3 January 01, 2022, 10:20:41 PM
4 January 02, 2022, 05:47:35 AM
5 January 02, 2022, 01:14:28 PM
6 January 02, 2022, 08:41:22 PM
7 January 03, 2022, 04:08:16 AM
8 January 03, 2022, 11:35:10 AM
9 January 03, 2022, 07:02:04 PM
10 January 04, 2022, 02:28:57 AM
11 January 04, 2022, 09:55:51 AM
12 January 04, 2022, 05:22:45 PM
13 January 05, 2022, 12:49:39 AM
14 January 05, 2022, 08:16:33 AM
15 January 05, 2022, 03:43:26 PM
16 January 05, 2022, 11:10:20 PM
17 January 06, 2022, 06:37:14 AM
18 January 06, 2022, 02:04:08 PM
19 January 06, 2022, 09:31:02 PM
20 January 07, 2022, 04:57:55 AM
21 January 07, 2022, 12:24:49 PM
22 January 07, 2022, 07:51:43 PM
23 January 08, 2022, 03:18:37 AM
24 January 08, 2022, 10:45:31 AM
25 January 08, 2022, 06:12:24 PM
26 January 09, 2022, 01:39:18 AM
27 January 09, 2022, 09:06:12 AM
28 January 09, 2022, 04:33:06 PM
29 January 10, 2022, 12:00:00 AM
dtype: object