如何按定义的时间间隔对 pandas 数据框进行分组? [英] How to group a pandas dataframe by a defined time interval?

问题描述

我有一个这样的数据框，我想每 60 分钟分组一次，从 06:30 开始分组.

I have a dataFrame like this, I would like to group every 60 minutes and start grouping at 06:30.

                           data
index
2017-02-14 06:29:57    11198648
2017-02-14 06:30:01    11198650
2017-02-14 06:37:22    11198706
2017-02-14 23:11:13    11207728
2017-02-14 23:21:43    11207774
2017-02-14 23:22:36    11207776

我正在使用:

df.groupby(pd.TimeGrouper(freq='60Min'))

我得到了这个分组:

                      data
index       
2017-02-14 06:00:00     x1
2017-02-14 07:00:00     x2
2017-02-14 08:00:00     x3
2017-02-14 09:00:00     x4
2017-02-14 10:00:00     x5

但我正在寻找这个结果:

but I am looking for this result:

                      data
index       
2017-02-14 06:30:00     x1
2017-02-14 07:30:00     x2
2017-02-14 08:30:00     x3
2017-02-14 09:30:00     x4
2017-02-14 10:30:00     x5

我怎样才能让函数在 6:30 开始以一小时为间隔进行分组?

How can I tell the function to start grouping at 6:30 at one-hour intervals?

如果 .groupby(pd.TimeGrouper(freq='60Min')) 无法完成，最好的方法是什么?

If it can not be done by the .groupby(pd.TimeGrouper(freq='60Min')), how is the best way to do it?

提前致以敬意和感谢

推荐答案

将 base=30 与 pd.Grouper.

Use base=30 in conjunction with label='right' parameters in pd.Grouper.

指定 label='right' 使时间段从 6:30(较高侧)而不是 5:30 开始分组.此外，base 设置为 0 默认，因此需要将这些偏移 30 以考虑日期的前向传播.

Specifying label='right' makes the time-period to start grouping from 6:30 (higher side) and not 5:30. Also, base is set to 0 by default, hence the need to offset those by 30 to account for the forward propagation of dates.

假设，你想聚合每个子组的第一个元素，那么:

Suppose, you want to aggregate the first element of every sub-group, then:

df.groupby(pd.Grouper(freq='60Min', base=30, label='right')).first()
# same thing using resample - df.resample('60Min', base=30, label='right').first()

产量:

                           data
index                          
2017-02-14 06:30:00  11198648.0
2017-02-14 07:30:00  11198650.0
2017-02-14 08:30:00         NaN
2017-02-14 09:30:00         NaN
2017-02-14 10:30:00         NaN
2017-02-14 11:30:00         NaN
2017-02-14 12:30:00         NaN
2017-02-14 13:30:00         NaN
2017-02-14 14:30:00         NaN
2017-02-14 15:30:00         NaN
2017-02-14 16:30:00         NaN
2017-02-14 17:30:00         NaN
2017-02-14 18:30:00         NaN
2017-02-14 19:30:00         NaN
2017-02-14 20:30:00         NaN
2017-02-14 21:30:00         NaN
2017-02-14 22:30:00         NaN
2017-02-14 23:30:00  11207728.0

这篇关于如何按定义的时间间隔对 pandas 数据框进行分组?的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！