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# pandas.api.typing.Rolling.quantile

Rolling.quantile(q, interpolation='linear', numeric_only=False)

  Calculate the rolling quantile.

  Return the `q`-th quantile of the values in each rolling window. The `interpolation` parameter controls how quantiles falling between two data points are handled.

  Parameters:
    q float

      Quantile to compute. 0 <= quantile <= 1.

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

      This optional parameter specifies the interpolation method to use, when the desired quantile lies between two data points i and j:

      > - linear: i + (j - i) * fraction, where fraction is the fractional part of the index surrounded by i and j.

      > - lower: i.

      > - higher: j.

      > - nearest: i or j whichever is nearest.

      > - midpoint: (i + j) / 2.

    numeric_only bool, default False

      Include only float, int, boolean columns.

  Returns:
    Series or DataFrame

      Return type is the same as the original object with `np.float64` dtype.

  See also

  `Series.rolling`

    Calling rolling with Series data.

  `DataFrame.rolling`

    Calling rolling with DataFrames.

  `Series.quantile`

    Aggregating quantile for Series.

  `DataFrame.quantile`

    Aggregating quantile for DataFrame.

  Examples

      >>> s = pd.Series([1, 2, 3, 4])
      >>> s.rolling(2).quantile(0.4, interpolation="lower")
      0    NaN
      1    1.0
      2    2.0
      3    3.0
      dtype: float64

      >>> s.rolling(2).quantile(0.4, interpolation="midpoint")
      0    NaN
      1    1.5
      2    2.5
      3    3.5
      dtype: float64