pandas.NamedAgg

class pandas.NamedAgg(column, aggfunc, *args, **kwargs)

Helper for column specific aggregation with control over output column names.

Parameters:

columnHashable

Column label in the DataFrame to apply aggfunc.

aggfuncfunction or str

Function to apply to the provided column. If string, the name of a built-in pandas function.

*args, **kwargsAny

Optional positional and keyword arguments passed to aggfunc.

See also

DataFrame.groupby

Group DataFrame using a mapper or by a Series of columns.

Examples

>>> df = pd.DataFrame({"key": [1, 1, 2], "a": [-1, 0, 1], 1: [10, 11, 12]})
>>> agg_a = pd.NamedAgg(column="a", aggfunc="min")
>>> agg_1 = pd.NamedAgg(column=1, aggfunc=lambda x: np.mean(x))
>>> df.groupby("key").agg(result_a=agg_a, result_1=agg_1)
    result_a  result_1
key
1          -1      10.5
2           1      12.0

>>> def n_between(ser, low, high, **kwargs):
...     return ser.between(low, high, **kwargs).sum()

>>> agg_between = pd.NamedAgg("a", n_between, 0, 1)
>>> df.groupby("key").agg(count_between=agg_between)
    count_between
key
1               1
2               1

>>> agg_between_kw = pd.NamedAgg("a", n_between, 0, 1, inclusive="both")
>>> df.groupby("key").agg(count_between_kw=agg_between_kw)
    count_between_kw
key
1                   1
2                   1

Attributes

args

Methods