issues: 367493434

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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
367493434 MDExOlB1bGxSZXF1ZXN0MjIwOTA5OTkx 2470 fill_value in shift 5635139 closed 0     2 2018-10-06T20:33:29Z 2018-12-28T01:07:17Z 2018-12-27T22:58:30Z MEMBER   0 pydata/xarray/pulls/2470
  • [x] Closes #https://github.com/pydata/xarray/issues/2451
  • [x] Tests added
  • [x] Tests passed
  • [x] Fully documented, including whats-new.rst for all changes and api.rst for new API (remove if this change should not be visible to users, e.g., if it is an internal clean-up, or if this is part of a larger project that will be documented later)

Should we be more defensive around which fill_values can be passed? Currently, if the array and float values have incompatible dtypes, we don't preemtively warn or cast, apart from the case of np.nan, which then uses the default filler

 
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