pandas.core.groupby.DataFrameGroupBy.skew — pandas 2.2.3 documentation (original) (raw)

DataFrameGroupBy.skew(axis=<no_default>, skipna=True, numeric_only=False, **kwargs)[source]#

Return unbiased skew within groups.

Normalized by N-1.

Parameters:

axis{0 or ‘index’, 1 or ‘columns’, None}, default 0

Axis for the function to be applied on.

Specifying axis=None will apply the aggregation across both axes.

Added in version 2.0.0.

Deprecated since version 2.1.0: For axis=1, operate on the underlying object instead. Otherwise the axis keyword is not necessary.

skipnabool, default True

Exclude NA/null values when computing the result.

numeric_onlybool, default False

Include only float, int, boolean columns.

**kwargs

Additional keyword arguments to be passed to the function.

Returns:

DataFrame

See also

DataFrame.skew

Return unbiased skew over requested axis.

Examples

arrays = [['falcon', 'parrot', 'cockatoo', 'kiwi', ... 'lion', 'monkey', 'rabbit'], ... ['bird', 'bird', 'bird', 'bird', ... 'mammal', 'mammal', 'mammal']] index = pd.MultiIndex.from_arrays(arrays, names=('name', 'class')) df = pd.DataFrame({'max_speed': [389.0, 24.0, 70.0, np.nan, ... 80.5, 21.5, 15.0]}, ... index=index) df max_speed name class falcon bird 389.0 parrot bird 24.0 cockatoo bird 70.0 kiwi bird NaN lion mammal 80.5 monkey mammal 21.5 rabbit mammal 15.0 gb = df.groupby(["class"]) gb.skew() max_speed class bird 1.628296 mammal 1.669046 gb.skew(skipna=False) max_speed class bird NaN mammal 1.669046