pandas.core.groupby.DataFrameGroupBy.quantile#

DataFrameGroupBy.quantile(q=0.5, interpolation='linear', numeric_only=False)[source]#

Return group values at the given quantile, a la numpy.percentile.

Parameters:
qfloat or array-like, default 0.5 (50% quantile)

Value(s) between 0 and 1 providing the quantile(s) to compute.

interpolation{‘linear’, ‘lower’, ‘higher’, ‘midpoint’, ‘nearest’}

Method to use when the desired quantile falls between two points.

numeric_onlybool, default False

Include only float, int or boolean data.

New in version 1.5.0.

Changed in version 2.0.0: numeric_only now defaults to False.

Returns:
Series or DataFrame

Return type determined by caller of GroupBy object.

See also

Series.quantile

Similar method for Series.

DataFrame.quantile

Similar method for DataFrame.

numpy.percentile

NumPy method to compute qth percentile.

Examples

>>> df = pd.DataFrame(
...     [["a", 1], ["a", 2], ["a", 3], ["b", 1], ["b", 3], ["b", 5]],
...     columns=["key", "val"],
... )
>>> df.groupby("key").quantile()
    val
key
a    2.0
b    3.0