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

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.


q : float in range of [0,1] (or sequence 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.


quantiles : Dataset

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.