在应用函数pandas python中包含组名 [英] Including the group name in the apply function pandas python

问题描述

是否可以指定 groupby() 调用在 apply() lambda 函数中使用组名?

Is there away to specify to the groupby() call to use the group name in the apply() lambda function?

类似于如果我遍历组，我可以通过以下元组分解获得组键:

Similar to if I iterate through groups I can get the group key via the following tuple decomposition:

for group_name, subdf in temp_dataframe.groupby(level=0, axis=0):
    print group_name

...有没有办法在apply函数中也得到组名，比如:

...is there a way to also get the group name in the apply function, such as:

temp_dataframe.groupby(level=0,axis=0).apply(lambda group_name, subdf: foo(group_name, subdf)

如何获取组名作为 apply lambda 函数的参数?

How can I get the group name as an argument for the apply lambda function?

推荐答案

我认为你应该可以使用 name 属性:

I think you should be able to use the nameattribute:

temp_dataframe.groupby(level=0,axis=0).apply(lambda x: foo(x.name, x))

应该可以，例如:

In [132]:
df = pd.DataFrame({'a':list('aabccc'), 'b':np.arange(6)})
df

Out[132]:
   a  b
0  a  0
1  a  1
2  b  2
3  c  3
4  c  4
5  c  5

In [134]:
df.groupby('a').apply(lambda x: print('name:', x.name, '\nsubdf:',x))

name: a 
subdf:    a  b
0  a  0
1  a  1
name: b 
subdf:    a  b
2  b  2
name: c 
subdf:    a  b
3  c  3
4  c  4
5  c  5
Out[134]:
Empty DataFrame
Columns: []
Index: []

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