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# pandas.api.typing.Resampler.quantile

final Resampler.quantile(q=0.5, **kwargs)

  Return value at the given quantile.

  Computes the quantile of values within each resampled group.

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

      Value between 0 <= q <= 1, the quantile(s) to compute.

    **kwargs

      Additional keyword arguments to be passed to the function.

  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(0.25)
      2023-01-01    1.5
      2023-02-01    3.5
      Freq: MS, dtype: float64