从 numpy.timedelta64 值中提取天数

问题描述

限时删除！！

我正在使用 pandas/python 并且我有两个日期时间序列 s1 和 s2，它们是在包含日期/时间的 df 字段上使用to_datetime"函数生成的.

当我从 s2 中减去 s1

s3 = s2 - s1

我得到一个系列 s3，类型为

timedelta64[ns]

0 385 天，04:10:361 57 天，22:54:002 642 天，21:15:233 615 天，00:55:444 160 天，22:13:355 196 天，23:06:496 23 天，22:57:177 2 天，22:17:318 622 天，01:29:259 79 天，20:15:1410 23 天，22:46:5111 268 天，19:23:0412 钠盐13 纳特14 583 天，03:40:39

我如何看待系列的 1 个元素:

s3[10]

我得到了这样的东西:

numpy.timedelta64(2069211000000000,'ns')

如何从 s3 中提取天数并将它们保留为整数(对小时/分钟等不太感兴趣)?

在此先感谢您的帮助.

解决方案

您可以将其转换为具有日期精度的 timedelta.要提取天数的整数值，请将其除以一天的时间增量.

>>>x = np.timedelta64(2069211000000000, 'ns')>>>days = x.astype('timedelta64[D]')>>>天数/np.timedelta64(1, 'D')23

或者，正如@PhillipCloud 建议的那样，只是 days.astype(int)，因为 timedelta 只是一个 64 位整数，根据第二个参数以各种方式解释你传入 ('D', 'ns', ...).

您可以在此处找到更多相关信息.

I am using pandas/python and I have two date time series s1 and s2, that have been generated using the 'to_datetime' function on a field of the df containing dates/times.

When I subtract s1 from s2

I get a series, s3, of type

0    385 days, 04:10:36
1     57 days, 22:54:00
2    642 days, 21:15:23
3    615 days, 00:55:44
4    160 days, 22:13:35
5    196 days, 23:06:49
6     23 days, 22:57:17
7      2 days, 22:17:31
8    622 days, 01:29:25
9     79 days, 20:15:14
10    23 days, 22:46:51
11   268 days, 19:23:04
12                  NaT
13                  NaT
14   583 days, 03:40:39

How do I look at 1 element of the series:

I get something like this:

How do I extract days from s3 and maybe keep them as integers(not so interested in hours/mins etc.)?

Thanks in advance for any help.

解决方案

You can convert it to a timedelta with a day precision. To extract the integer value of days you divide it with a timedelta of one day.

>>> x = np.timedelta64(2069211000000000, 'ns')
>>> days = x.astype('timedelta64[D]')
>>> days / np.timedelta64(1, 'D')
23

Or, as @PhillipCloud suggested, just days.astype(int) since the timedelta is just a 64bit integer that is interpreted in various ways depending on the second parameter you passed in ('D', 'ns', ...).

You can find more about it here.

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