xarray.DataArray.quantile

DataArray.quantile(q: Any, dim: Union[Hashable, Sequence[Hashable], None] = None, interpolation: str = 'linear', keep_attrs: bool = None) → xarray.core.dataarray.DataArray

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

Returns the qth quantiles(s) of the array elements.

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 (hashable or sequence of hashable, 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.
Returns:

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

Return type:

DataArray

See also

numpy.nanpercentile(), pandas.Series.quantile(), Dataset.quantile()