docs

doc/user-guide/dask.rst

@@ -259,18 +259,16 @@ along a particular dimension, an exception is raised when you try to access
     arrays in a dataset share the same chunking alignment. Neither of these
     are currently done.
 
-NumPy ufuncs like ``np.sin`` currently only work on eagerly evaluated arrays
-(this will change with the next major NumPy release). We have provided
-replacements that also work on all xarray objects, including those that store
-lazy Dask arrays, in the :ref:`xarray.ufuncs <api.ufuncs>` module:
+NumPy ufuncs like ``np.sin`` transparently work on all xarray objects, including those
+that store lazy Dask arrays:
 
 .. ipython:: python
 
-    import xarray.ufuncs as xu
+    import numpy as np
 
-    xu.sin(rechunked)
+    np.sin(rechunked)
 
-To access Dask arrays directly, use the new
+To access Dask arrays directly, use the
 :py:attr:`DataArray.data <xarray.DataArray.data>` attribute. This attribute exposes
 array data either as a Dask array or as a NumPy array, depending on whether it has been
 loaded into Dask or not:
@@ -281,8 +279,8 @@ loaded into Dask or not:
 
 .. note::
 
-    In the future, we may extend ``.data`` to support other "computable" array
-    backends beyond Dask and NumPy (e.g., to support sparse arrays).
+    ``.data`` is also used to expose other "computable" array backends beyond Dask and
+    NumPy (e.g. sparse and pint arrays).
 
 .. _dask.automatic-parallelization: