pandas.core.groupby.SeriesGroupBy.quantile#

SeriesGroupBy.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