因果重采样:最后一个X< time_unit>之和 [英] Causal resampling: Sum over the last X <time_unit>

问题描述

说我有以下值:

                                   money_spent
time                 
2014-10-06 17:59:40.016000-04:00      1.832128
2014-10-06 17:59:41.771000-04:00      2.671048
2014-10-06 17:59:43.001000-04:00      2.019434
2014-10-06 17:59:44.792000-04:00      1.294051
2014-10-06 17:59:48.741000-04:00      0.867856

我希望衡量每2秒花费的钱.更具体地说，对于输出中的每个时间戳，我都需要查看最近2秒钟内花费的钱.

I am hoping to measure much money is spent every 2 seconds. More specifically, for every timestamp in the output, I need to see the money spent within the last 2 seconds.

当我这样做时:

df.resample('2S', how='last')

我得到:

                                money_spent
time               
2014-10-06 17:59:40-04:00          2.671048
2014-10-06 17:59:42-04:00          2.019434
2014-10-06 17:59:44-04:00          1.294051
2014-10-06 17:59:46-04:00               NaN
2014-10-06 17:59:48-04:00          0.867856

这不是我期望的.首先，请注意，重新采样的df中的第一个条目是 2.671048 ，但这是在17:59:40时间，即使根据原始数据框架，没有花任何钱还.那怎么可能?

which is not what I would expect. To start with, note that the first entry in the resampled df is 2.671048, but that is at time 17:59:40, even though, according to the original dataframe, no money was spent yet. How is that possible?

推荐答案

尝试使用how=np.sum:

df.resample('2S', how=np.sum, closed='left', label='right')

修改:

对于closed和label:

表示:从左封闭的间隔开始，并用间隔右端的日期标记. (共2秒，例如[1、1.2、1.5、1.9、2)). 然后从 docs :

It means: from the left-closed interval, and labeled with the date from the right end of the interval. (of 2 seconds e.g. [1, 1.2, 1.5, 1.9, 2) ) . And from the docs:

已关闭:{'right'，'left'}箱间隔的哪一侧已关闭

closed : {‘right’, ‘left’} Which side of bin interval is closed

label:{'right'，'left'}哪个桶边标签用来标记存储桶

label : {‘right’, ‘left’} Which bin edge label to label bucket with

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