pandas 使用特定的开始时间重新采样每小时的 TimeSeries

Resample hourly TimeSeries with certain starting hour

提问by MaM

I want to resample a TimeSeries in daily (exactly 24 hours) frequence starting at a certain hour.

我想从某个小时开始以每天（恰好 24 小时）的频率重新采样 TimeSeries。

Like:

喜欢：

index = date_range(datetime(2012,1,1,17), freq='H', periods=60)

ts = Series(data=[1]*60, index=index)

ts.resample(rule='D', how='sum', closed='left', label='left')

Result i get:

我得到的结果：

2012-01-01  7
2012-01-02 24
2012-01-03 24
2012-01-04  5
Freq: D

Result i wish:

我希望的结果：

2012-01-01 17:00:00 24
2012-01-02 17:00:00 24
2012-01-03 17:00:00 12
Freq: D

Some weeks ago you could pass '24H'to the freqargument and it worked totally fine. But now it combines '24H'to '1D'.

几个星期前，你可以传递'24H'给这个freq论点，它工作得很好。但现在它结合'24H'到'1D'.

Was I using a bug with '24H'which is fixed now? And how can i get the wished result in a efficient and pythonic (or pandas) way back?

我是否使用了'24H'现在已修复的错误？我怎样才能以高效且 Pythonic（或 Pandas）的方式获得预期的结果？

versions:

版本：

• python 2.7.3
• pandas 0.9.0rc1 (but doesn't work in 0.8.1, too)
• numpy 1.6.1

• 蟒蛇 2.7.3
• pandas 0.9.0rc1（但在 0.8.1 中也不起作用）
• 麻木 1.6.1

回答by Andy Hayden

Resamplehas an baseargument which covers this case:

Resample有一个base论据涵盖了这种情况：

ts.resample(rule='24H', closed='left', label='left', base=17).sum()

Output:

输出：

2012-01-01 17:00:00    24
2012-01-02 17:00:00    24
2012-01-03 17:00:00    12
Freq: 24H

回答by Thomas G.

2020 Update: for dataframes

2020 年更新：用于数据帧

Use the basekeyword as referred in the doc:

使用文档中base提到的关键字：

Code example:

代码示例：

df.resample(pd.Timedelta('24 hours'), # or '24H'
 base=17 # <--  ADD THIS
).sum()