issues: 539988974

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id node_id number title user state locked assignee milestone comments created_at updated_at closed_at author_association active_lock_reason draft pull_request body reactions performed_via_github_app state_reason repo type
539988974 MDExOlB1bGxSZXF1ZXN0MzU0ODcyNjU3 3643 Pint support for DataArray 14808389 closed 0     24 2019-12-18T23:49:29Z 2020-04-29T16:12:35Z 2020-04-29T16:12:24Z MEMBER   0 pydata/xarray/pulls/3643

This is part of the effort to add support for pint (see #3594) on DataArray. This depends on #3611, so we should merge that first.

  • [x] Tests added
  • [x] Passes black . && mypy . && flake8
  • [x] Fully documented, including whats-new.rst for all changes and api.rst for new API

list of failing tests from #3594: - __init__: Needs unit support in IndexVariable, blocked by #1603 - aggregation: + pint currently does not implement prod + calling np.median returns a numpy scalar instead of a DataArray because DataArray does not implement __array_function__ + everything else works - bivariate ufuncs: fixed by hgrecco/pint#951 (but the unit won't be correct if the array is not passed first. See hgrecco/pint#1019) - numpy methods: rank only works with numpy.ndarray (uses bottleneck) - ffill, bfill: uses bottleneck, which does not support NEP-18? - where: works (but the choice of treating array(nan) and array(0) as special needs to be discussed) - interpolate_na: enforces the use of numpy.vectorize which does not support NEP18 - combine_first: works, but does not test indexing (which should fail) - equals, identical: works (right now identical returns the same as equals) - drop_sel, sel, loc: indexes strip units (#1603) - interp: uses scipy.interpolate.interp1d which strips units - interp_like: same as interp - to_unstacked_dataset: blocked by IndexVariable - quantile: works (but needs a new pint version since it uses numpy.nanquantile - rolling: uses numpy.lib.stride_tricks.as_strided which is not supported by NEP18 - rolling_exp: numbagg

 
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