bigframes.pandas.api.typing.SeriesGroupBy.quantile

SeriesGroupBy.quantile(q: float | Sequence[float] = 0.5, *, numeric_only: bool = False) → Series

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

Examples:

>>> import bigframes.pandas as bpd
>>> df = bpd.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

[2 rows x 1 columns]

Parameters:

• q (float or array-like, default 0.5 (50% quantile)) – Value(s) between 0 and 1 providing the quantile(s) to compute.

• numeric_only (bool, default False) – Include only float, int or boolean data.

Returns:

Return type determined by caller of GroupBy object.

Return type:

bigframes.pandas.DataFrame or bigframes.pandas.Series