xarray.Dataset.quantile

Dataset.quantile(q, dim=None, interpolation='linear', numeric_only=False, keep_attrs=None)

Compute the qth quantile of the data along the specified dimension.

Returns the qth quantiles(s) of the array elements for each variable in the Dataset.

Parameters:
  • q (float in range of [0,1] or array-like of floats) – Quantile to compute, which must be between 0 and 1 inclusive.
  • dim (str or sequence of str, optional) – Dimension(s) over which to apply quantile.
  • 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 < 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.
  • keep_attrs (bool, optional) – If True, the dataset’s attributes (attrs) will be copied from the original object to the new one. If False (default), the new object will be returned without attributes.
  • numeric_only (bool, optional) – If True, only apply func to variables with a numeric dtype.
Returns:

quantiles – If q is a single quantile, then the result is a scalar for each variable in data_vars. If multiple percentiles are given, first axis of the result corresponds to the quantile and a quantile dimension is added to the return Dataset. The other dimensions are the dimensions that remain after the reduction of the array.

Return type:

Dataset

See also

numpy.nanquantile(), pandas.Series.quantile(), DataArray.quantile()

Examples

>>> ds = xr.Dataset(
...     {"a": (("x", "y"), [[0.7, 4.2, 9.4, 1.5], [6.5, 7.3, 2.6, 1.9]])},
...     coords={"x": [7, 9], "y": [1, 1.5, 2, 2.5]},
... )
>>> ds.quantile(0)  # or ds.quantile(0, dim=...)
<xarray.Dataset>
Dimensions:   ()
Coordinates:
    quantile  float64 0.0
Data variables:
    a         float64 0.7
>>> ds.quantile(0, dim="x")
<xarray.Dataset>
Dimensions:   (y: 4)
Coordinates:
  * y         (y) float64 1.0 1.5 2.0 2.5
    quantile  float64 0.0
Data variables:
    a         (y) float64 0.7 4.2 2.6 1.5
>>> ds.quantile([0, 0.5, 1])
<xarray.Dataset>
Dimensions:   (quantile: 3)
Coordinates:
  * quantile  (quantile) float64 0.0 0.5 1.0
Data variables:
    a         (quantile) float64 0.7 3.4 9.4
>>> ds.quantile([0, 0.5, 1], dim="x")
<xarray.Dataset>
Dimensions:   (quantile: 3, y: 4)
Coordinates:
  * y         (y) float64 1.0 1.5 2.0 2.5
  * quantile  (quantile) float64 0.0 0.5 1.0
Data variables:
    a         (quantile, y) float64 0.7 4.2 2.6 1.5 3.6 ... 1.7 6.5 7.3 9.4 1.9