pandas.core.resample.Resampler.quantile#

final Resampler.quantile(q=0.5, **kwargs)[source]#

Return value at the given quantile.

Parameters:

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

Returns:

DataFrame or Series: Quantile of values within each group.

See also

Series.quantile: Return a series, where the index is q and the values are the quantiles.
DataFrame.quantile: Return a DataFrame, where the columns are the columns of self, and the values are the quantiles.
DataFrameGroupBy.quantile: Return a DataFrame, where the columns are groupby columns, and the values are its quantiles.

Examples

>>> ser = pd.Series([1, 3, 2, 4, 3, 8],
...                 index=pd.DatetimeIndex(['2023-01-01',
...                                         '2023-01-10',
...                                         '2023-01-15',
...                                         '2023-02-01',
...                                         '2023-02-10',
...                                         '2023-02-15']))
>>> ser.resample('MS').quantile()
2023-01-01    2.0
2023-02-01    4.0
Freq: MS, dtype: float64

>>> ser.resample('MS').quantile(.25)
2023-01-01    1.5
2023-02-01    3.5
Freq: MS, dtype: float64