GroupBy objects

Dataset

DatasetGroupBy(obj, groupers[, ...])
DatasetGroupBy.map(func[, args, shortcut])	Apply a function to each Dataset in the group and concatenate them together into a new Dataset.
DatasetGroupBy.reduce(func[, dim, axis, ...])	Reduce the items in this group by applying func along some dimension(s).
DatasetGroupBy.assign(**kwargs)	Assign data variables by group.
DatasetGroupBy.assign_coords([coords])	Assign coordinates by group.
DatasetGroupBy.first([skipna, keep_attrs])	Return the first element of each group along the group dimension
DatasetGroupBy.last([skipna, keep_attrs])	Return the last element of each group along the group dimension
DatasetGroupBy.fillna(value)	Fill missing values in this object by group.
DatasetGroupBy.quantile(q[, dim, method, ...])	Compute the qth quantile over each array in the groups and concatenate them together into a new array.
DatasetGroupBy.where(cond[, other])	Return elements from self or other depending on cond.
DatasetGroupBy.all([dim, keep_attrs])	Reduce this Dataset's data by applying all along some dimension(s).
DatasetGroupBy.any([dim, keep_attrs])	Reduce this Dataset's data by applying any along some dimension(s).
DatasetGroupBy.count([dim, keep_attrs])	Reduce this Dataset's data by applying count along some dimension(s).
DatasetGroupBy.cumsum([dim, skipna, keep_attrs])	Reduce this Dataset's data by applying cumsum along some dimension(s).
DatasetGroupBy.cumprod([dim, skipna, keep_attrs])	Reduce this Dataset's data by applying cumprod along some dimension(s).
DatasetGroupBy.max([dim, skipna, keep_attrs])	Reduce this Dataset's data by applying max along some dimension(s).
DatasetGroupBy.mean([dim, skipna, keep_attrs])	Reduce this Dataset's data by applying mean along some dimension(s).
DatasetGroupBy.median([dim, skipna, keep_attrs])	Reduce this Dataset's data by applying median along some dimension(s).
DatasetGroupBy.min([dim, skipna, keep_attrs])	Reduce this Dataset's data by applying min along some dimension(s).
DatasetGroupBy.prod([dim, skipna, ...])	Reduce this Dataset's data by applying prod along some dimension(s).
DatasetGroupBy.std([dim, skipna, ddof, ...])	Reduce this Dataset's data by applying std along some dimension(s).
DatasetGroupBy.sum([dim, skipna, min_count, ...])	Reduce this Dataset's data by applying sum along some dimension(s).
DatasetGroupBy.var([dim, skipna, ddof, ...])	Reduce this Dataset's data by applying var along some dimension(s).
DatasetGroupBy.dims
DatasetGroupBy.groups	Mapping from group labels to indices.
DatasetGroupBy.shuffle_to_chunks([chunks])	Sort or "shuffle" the underlying object.

DataArray

DataArrayGroupBy(obj, groupers[, ...])
DataArrayGroupBy.map(func[, args, shortcut])	Apply a function to each array in the group and concatenate them together into a new array.
DataArrayGroupBy.reduce(func[, dim, axis, ...])	Reduce the items in this group by applying func along some dimension(s).
DataArrayGroupBy.assign_coords([coords])	Assign coordinates by group.
DataArrayGroupBy.first([skipna, keep_attrs])	Return the first element of each group along the group dimension
DataArrayGroupBy.last([skipna, keep_attrs])	Return the last element of each group along the group dimension
DataArrayGroupBy.fillna(value)	Fill missing values in this object by group.
DataArrayGroupBy.quantile(q[, dim, method, ...])	Compute the qth quantile over each array in the groups and concatenate them together into a new array.
DataArrayGroupBy.where(cond[, other])	Return elements from self or other depending on cond.
DataArrayGroupBy.all([dim, keep_attrs])	Reduce this DataArray's data by applying all along some dimension(s).
DataArrayGroupBy.any([dim, keep_attrs])	Reduce this DataArray's data by applying any along some dimension(s).
DataArrayGroupBy.count([dim, keep_attrs])	Reduce this DataArray's data by applying count along some dimension(s).
DataArrayGroupBy.cumsum([dim, skipna, ...])	Reduce this DataArray's data by applying cumsum along some dimension(s).
DataArrayGroupBy.cumprod([dim, skipna, ...])	Reduce this DataArray's data by applying cumprod along some dimension(s).
DataArrayGroupBy.max([dim, skipna, keep_attrs])	Reduce this DataArray's data by applying max along some dimension(s).
DataArrayGroupBy.mean([dim, skipna, keep_attrs])	Reduce this DataArray's data by applying mean along some dimension(s).
DataArrayGroupBy.median([dim, skipna, ...])	Reduce this DataArray's data by applying median along some dimension(s).
DataArrayGroupBy.min([dim, skipna, keep_attrs])	Reduce this DataArray's data by applying min along some dimension(s).
DataArrayGroupBy.prod([dim, skipna, ...])	Reduce this DataArray's data by applying prod along some dimension(s).
DataArrayGroupBy.std([dim, skipna, ddof, ...])	Reduce this DataArray's data by applying std along some dimension(s).
DataArrayGroupBy.sum([dim, skipna, ...])	Reduce this DataArray's data by applying sum along some dimension(s).
DataArrayGroupBy.var([dim, skipna, ddof, ...])	Reduce this DataArray's data by applying var along some dimension(s).
DataArrayGroupBy.dims
DataArrayGroupBy.groups	Mapping from group labels to indices.
DataArrayGroupBy.shuffle_to_chunks([chunks])	Sort or "shuffle" the underlying object.

Grouper Objects

groupers.BinGrouper(bins[, right, labels, ...])	Grouper object for binning numeric data.
groupers.UniqueGrouper([labels])	Grouper object for grouping by a categorical variable.
groupers.TimeResampler(freq[, closed, ...])	Grouper object specialized to resampling the time coordinate.
groupers.SeasonGrouper(seasons)	Allows grouping using a custom definition of seasons.
groupers.SeasonResampler(seasons, *[, ...])	Allows grouping using a custom definition of seasons.