Closed
Description
Virtually everywhere we allow strings to substitue for functions in .agg, .apply and such, straightforward to add here. Just need to call https://github.com/pandas-dev/pandas/blob/master/pandas/core/base.py#L627.
example from pd.pivot_table doc-string
In [11]: >>> df = pd.DataFrame({"A": ["foo", "foo", "foo", "foo", "foo",
...: ... "bar", "bar", "bar", "bar"],
...: ... "B": ["one", "one", "one", "two", "two",
...: ... "one", "one", "two", "two"],
...: ... "C": ["small", "large", "large", "small",
...: ... "small", "large", "small", "small",
...: ... "large"],
...: ... "D": [1, 2, 2, 3, 3, 4, 5, 6, 7]})
...:
In [12]: df
Out[12]:
A B C D
0 foo one small 1
1 foo one large 2
2 foo one large 2
3 foo two small 3
4 foo two small 3
5 bar one large 4
6 bar one small 5
7 bar two small 6
8 bar two large 7
works
In [13]: pd.pivot_table(df, values='D', index=['A', 'B'],
...: columns=['C'], aggfunc=[np.sum, np.mean])
Out[13]:
sum mean
C large small large small
A B
bar one 4.0 5.0 4.0 5.0
two 7.0 6.0 7.0 6.0
foo one 4.0 1.0 2.0 1.0
two NaN 6.0 NaN 3.0
fails
In [14]: pd.pivot_table(df, values='D', index=['A', 'B'],
...: columns=['C'], aggfunc=['sum', 'mean'])
AttributeError: 'str' object has no attribute '__name__'