# xarray.DataArray.quantile¶

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

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