xarray.core.weighted.DatasetWeighted#

class xarray.core.weighted.DatasetWeighted(obj, weights)[source]#
__init__(obj, weights)[source]#

Create a Weighted object

Parameters:

  • obj (DataArray or Dataset) – Object over which the weighted reduction operation is applied.

  • weights (DataArray) – An array of weights associated with the values in the obj. Each value in the obj contributes to the reduction operation according to its associated weight.

Notes

weights must be a DataArray and cannot contain missing values. Missing values can be replaced by weights.fillna(0).

Methods

__init__(obj, weights)

Create a Weighted object

mean([dim, skipna, keep_attrs])

Reduce this Dataset's data by a weighted mean along some dimension(s).

quantile(q, *[, dim, keep_attrs, skipna])

Apply a weighted quantile to this Dataset's data along some dimension(s).

std([dim, skipna, keep_attrs])

Reduce this Dataset's data by a weighted std along some dimension(s).

sum([dim, skipna, keep_attrs])

Reduce this Dataset's data by a weighted sum along some dimension(s).

sum_of_squares([dim, skipna, keep_attrs])

Reduce this Dataset's data by a weighted sum_of_squares along some dimension(s).

sum_of_weights([dim, keep_attrs])

Calculate the sum of weights, accounting for missing values in the data.

var([dim, skipna, keep_attrs])

Reduce this Dataset's data by a weighted var along some dimension(s).

Attributes

obj

weights