组多索引 pandas 数据框 [英] group multi-index pandas dataframe

问题描述

是否可以将多索引(2个级别)熊猫数据帧按多个索引级别之一分组?

Is it possible to groupby a multi-index (2 levels) pandas dataframe by one of the multi-index levels ?

我知道的唯一方法是在多索引上重置reset_index，然后再次设置索引.我相信有更好的方法可以做到，而且我想知道如何做.

The only way I know of doing it is to reset_index on a multiindex and then set index again. I am sure there is a better way to do it, and I want to know how.

推荐答案

是的，请使用level参数.在此处看看.示例:

Yes, use the level parameter. Take a look here. Example:

In [26]: s

first  second  third
bar    doo     one      0.404705
               two      0.577046
baz    bee     one     -1.715002
               two     -1.039268
foo    bop     one     -0.370647
               two     -1.157892
qux    bop     one     -1.344312
               two      0.844885
dtype: float64

In [27]: s.groupby(level=['first','second']).sum()

first  second
bar    doo       0.981751
baz    bee      -2.754270
foo    bop      -1.528539
qux    bop      -0.499427
dtype: float64

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