xarray.Dataset.quantile

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

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.

• skipna (bool, optional) – Whether to skip missing values when aggregating.

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(), numpy.quantile(), 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