pandas.NamedAgg — pandas 3.0.0rc0+33.g1fd184de2a documentation (original) (raw)

class pandas.NamedAgg(column, aggfunc, *args, **kwargs)[source]#

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.

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

Methods