pandas 时间序列resample

resample与groupby的区别：
resample：在给定的时间单位内重取样
groupby：对给定的数据条目进行统计

函数原型：
DataFrame.resample(rule, how=None, axis=0, fill_method=None, closed=None, label=None, convention=‘start‘, kind=None, loffset=None, limit=None, base=0)
其中，参数how已经废弃了。

下面开始练习

import numpy as np
import pandas as pd

Start by creating a series with 9 one minute timestamps.

index = pd.date_range(‘1/1/2000‘, periods=9, freq=‘T‘)
series = pd.Series(range(9), index=index)

Downsample the series into 3 minute bins and sum the values of the timestamps falling into a bin.

series.resample(‘3T‘).sum()

To include this value close the right side of the bin interval as illustrated in the example below this one.

series.resample(‘3T‘, label=‘right‘).sum()

Downsample the series into 3 minute bins as above, but close the right side of the bin interval.

series.resample(‘3T‘, label=‘right‘, closed=‘right‘).sum()

Upsample the series into 30 second bins.

series.resample(‘30S‘).asfreq()

Upsample the series into 30 second bins and fill the NaN values using the pad method.

series.resample(‘30S‘).pad()

Upsample the series into 30 second bins and fill the NaN values using the bfill method.

series.resample(‘30S‘).bfill()

Pass a custom function via apply

def custom_resampler(array_like):
    return np.sum(array_like)+5

series.resample(‘3T‘).apply(custom_resampler)

附：常见时间频率
A year
M month
W week
D day
H hour
T minute
S second