API Reference

Functions

groupby_reduce(array, *by, func[, ...])	GroupBy reductions using tree reductions for dask.array
groupby_scan(array, *by, func[, ...])	GroupBy reductions using parallel scans for dask.array
xarray.xarray_reduce(obj, *by, func[, ...])	GroupBy reduce operations on xarray objects using numpy-groupies.

Rechunking

rechunk_for_blockwise(array, axis, labels, *)	Rechunks array so that group boundaries line up with chunk boundaries, allowing embarrassingly parallel group reductions.
rechunk_for_cohorts(array, axis, labels, ...)	Rechunks array so that each new chunk contains groups that always occur together.
xarray.rechunk_for_blockwise(obj, dim, labels)	Rechunks array so that group boundaries line up with chunk boundaries, allowing embarrassingly parallel group reductions.
xarray.rechunk_for_cohorts(obj, dim, labels, ...)	Rechunks array so that each new chunk contains groups that always occur together.

Visualization

visualize.draw_mesh(nrow, ncol, *[, ...])
visualize.visualize_groups_1d(array, labels)	Visualize group distribution for a 1D array of group labels.
visualize.visualize_cohorts_2d(by, chunks)

Aggregation Objects

Aggregation(name, *[, numpy, preprocess, ...])
Scan(name, binary_op, scan, reduction, identity)
aggregations.sum_
aggregations.nansum