pandas 多索引分组依据 [英] Pandas Multiindex Groupby on Columns

问题描述

无论如何，在Multiindex的列上是否可以使用groupby.我知道您可以在行上找到一个很好的文档在这方面.但是我似乎无法按列分组.我唯一的解决方案是转置数据框.

Is there anyway to use groupby on the columns in a Multiindex. I know you can on the rows and there is good documentation in that regard. However I cannot seem to groupby on columns. The only solution I have is transposing the dataframe.

#generate data (copied from pandas example)
arrays=[['bar', 'bar', 'baz', 'baz', 'foo', 'foo', 'qux', 'qux'],['one', 'two', 'one', 'two', 'one', 'two', 'one', 'two']]
tuples = list(zip(*arrays))
index = pd.MultiIndex.from_tuples(tuples, names=['first', 'second'])
df = pd.DataFrame(np.random.randn(3, 8), index=['A', 'B', 'C'], columns=index)

现在，我将尝试对失败的列进行分组

Now I will try to groupby columns which fails

df.groupby(level=1)
df.groupby(level='first')

但是与行进行转置是可行的

However transposing with rows works

df.T.groupby(level=1)
df.T.groupby(level='first')

那么有没有一种方法可以不进行转置?

So is there a way to do this without transposing?

推荐答案

您需要在groupby方法中指定轴:

You need to specify the axis in the groupby method:

df.groupby(level = 1, axis = 1).sum()

或者如果您是按0级分组的话:

Or if you mean groupby level 0:

df.groupby(level = 0, axis = 1).sum()

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