pandas.core.groupby.DataFrameGroupBy.skew — pandas 3.0.0.dev0+2103.g41968a550a documentation (original) (raw)

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

Return unbiased skew within groups.

Normalized by N-1.

Parameters:

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

Unbiased skew within groups.

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