Pandas drop group column after groupby.apply(..)

Question

        uid  iid  val
uid                 
1   1    1    5   5.5
2   3    1    4   3.5
2   2    1    4   3.5
2   7    1    4   3.5
2   9    1    4   3.5
2   11   1    4   3.5

From the dataframe above, I want to remove the first column, which is:

uid
1
2
2
2
2
2

and extract

    uid  iid  val

1    1    5   5.5
3    1    4   3.5
2    1    4   3.5
7    1    4   3.5
9    1    4   3.5
11   1    4   3.5

Can someone help?

Answer 1

You can avoid including the uid in the index in the first place by passing group_keys=False to the groupby

df.groupby('uid', group_keys=False).apply(lambda x: x.tail(len(x) // 5))

   uid  iid  val
4    1    5  5.5

Answer 2

Use reset_index or droplevel :

df = df.reset_index(level=0, drop=True)


df = df.reset_index(level='uid', drop=True)

Or:

df.index = df.index.droplevel(0)

Answer 3

您可以将as_index设置为False以从df中分组索引。

df.groupby('uid', as_index=False)