I ran into this unexplained behaviour with groupby when using group_keys=True (the default),
it's not clear why using x vs. x[:] causes the group_keys argument to be ignored.
In [86]: df = DataFrame({'key': [1, 1, 1, 2, 2, 2, 3, 3, 3],
...: 'value': range(9)})
...: df
Out[86]:
key value
0 1 0
1 1 1
2 1 2
3 2 3
4 2 4
5 2 5
6 3 6
7 3 7
8 3 8
In [87]: df.groupby('key', group_keys=True).apply(lambda x: x[:].key)
Out[87]:
key
1 0 1
1 1
2 1
2 3 2
4 2
5 2
3 6 3
7 3
8 3
Name: key, dtype: int64
In [88]: df.groupby('key', group_keys=True).apply(lambda x: x.key)
Out[88]:
0 1
1 1
2 1
3 2
4 2
5 2
6 3
7 3
8 3
Name: key, dtype: int64
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