小编use*_*264的帖子

TimeGrouper,熊猫

我使用TimeGrouperpandas.tseries.resample每月返回到6M的总和如下:

6m_return = monthly_return.groupby(TimeGrouper(freq='6M')).aggregate(numpy.sum)
Run Code Online (Sandbox Code Playgroud)

在哪里monthly_return:

2008-07-01    0.003626
2008-08-01    0.001373
2008-09-01    0.040192
2008-10-01    0.027794
2008-11-01    0.012590
2008-12-01    0.026394
2009-01-01    0.008564
2009-02-01    0.007714
2009-03-01   -0.019727
2009-04-01    0.008888
2009-05-01    0.039801
2009-06-01    0.010042
2009-07-01    0.020971
2009-08-01    0.011926
2009-09-01    0.024998
2009-10-01    0.005213
2009-11-01    0.016804
2009-12-01    0.020724
2010-01-01    0.006322
2010-02-01    0.008971
2010-03-01    0.003911
2010-04-01    0.013928
2010-05-01    0.004640
2010-06-01    0.000744
2010-07-01    0.004697
2010-08-01    0.002553
2010-09-01    0.002770
2010-10-01    0.002834
2010-11-01    0.002157
2010-12-01    0.001034
Run Code Online (Sandbox Code Playgroud)

6m_return就像:

2008-07-31    0.003626
2009-01-31    0.116907
2009-07-31    0.067688
2010-01-31    0.085986 …
Run Code Online (Sandbox Code Playgroud)

group-by dataframe pandas

23
推荐指数
2
解决办法
3万
查看次数

标签 统计

dataframe ×1

group-by ×1

pandas ×1