列上的 Pandas Multiindex Groupby
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Pandas Multiindex Groupby on Columns
提问by Bobe Kryant
Is there anyway to use groupby on the columns in a Multiindex. I know you can on the rows and there is good documentationin that regard. However I cannot seem to groupby on columns. The only solution I have is transposing the dataframe.
无论如何在多索引中的列上使用 groupby 。我知道你可以在行上，并且在这方面有很好的文档。但是我似乎无法对列进行分组。我唯一的解决方案是转置数据帧。
#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)
Now I will try to groupby columns which fails
现在我将尝试对失败的列进行分组
df.groupby(level=1)
df.groupby(level='first')
However transposing with rows works
然而，与行转置工作
df.T.groupby(level=1)
df.T.groupby(level='first')
So is there a way to do this without transposing?
那么有没有办法在不移调的情况下做到这一点？
回答by Psidom
You need to specify the axis in the groupbymethod:
您需要在groupby方法中指定轴：
df.groupby(level = 1, axis = 1).sum()
Or if you mean groupby level 0:
或者，如果您的意思是 groupby 级别 0：
df.groupby(level = 0, axis = 1).sum()
