重新采样熊猫时间序列以获得 bin 名称的结束时间戳？

Question

I generate a sample 5 minute time series:

index = pd.date_range('1/1/2000', periods=10, freq='5T')
data=range(10)
ser = pd.Series(data, index=index)

What it looks like:

2000-01-01 00:00:00    0.0
2000-01-01 00:05:00    1.0
2000-01-01 00:10:00    2.0
2000-01-01 00:15:00    3.0
2000-01-01 00:20:00    4.0
2000-01-01 00:25:00    5.0
2000-01-01 00:30:00    6.0
2000-01-01 00:35:00    7.0
2000-01-01 00:40:00    8.0
2000-01-01 00:45:00    9.0
Freq: 5T, dtype: float64

What I need

I would like to turn this time series into a 15 minute one and have each 15 minute value be the mean of the 5 minute values observed in that 15 min period, ie

2000-01-01 00:15:00    2.0   # i.e. mean(1, 2, 3)
2000-01-01 00:30:00    5.0   # i.e. mean(4, 5, 6)
2000-01-01 00:45:00    8.0   # i.e. mean(7, 8, 9)

Things I tried

If I resample this data into 15 minute buckets and call mean i get:

ser.resample('15T').mean()

2000-01-01 00:00:00    1.0
2000-01-01 00:15:00    4.0
2000-01-01 00:30:00    7.0
2000-01-01 00:45:00    9.0

which is not computing the means I want. If I add closed='right' to the resample call I get closer to the values I want but the timestamps are not right.

ser.resample('15T', closed='right').mean()
1999-12-31 23:45:00    0.0
2000-01-01 00:00:00    2.0
2000-01-01 00:15:00    5.0
2000-01-01 00:30:00    8.0
Freq: 15T, dtype: float64

Any suggestions?

Answer 1

You can use the label argument in resample ,

ser.resample('15T', label='right', closed='right').mean()

this shifts the label from the left (default) to the right of the resampled window. This is a more succinct than my somewhat clunky comment.