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id ▼ node_id number state locked title user body created_at updated_at closed_at merged_at merge_commit_sha assignee milestone draft head base author_association auto_merge repo url merged_by
263654744 MDExOlB1bGxSZXF1ZXN0MjYzNjU0NzQ0 2843 closed 0 Allow passing _FillValue=False in encoding for vlen str variables. DWesl 22566757 <!-- Feel free to remove check-list items aren't relevant to your change --> The documentation seems to imply that passing _FillValue=False in the encoding works to set no fill value for any value. These changes to `netCDF4_.py` and `h5netcdf_.py` seem to allow this for variables that are vlen strings (dtype `str` rather than `"S1"`): I have used the code-path in `netCDF4_.py` in real code and know that it at least allows the save to complete. Allowing _FillValue=False makes it easier to explicitly exclude `_FillValue` from being written for coordinate variables, which some CF-compliance checkers complain about. - [ ] Closes #xxxx - [X] Tests added - [ ] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API 2019-03-22T15:20:27Z 2019-03-30T14:04:30Z 2019-03-30T14:04:13Z   630e5af32173b0368ff3dce2340f0b94dee58b5a     0 101f261f1280b5f6b02be7899d77d969db096972 742ed3984f437982057fd46ecfb0bce214563cb8 CONTRIBUTOR   xarray 13221727 https://github.com/pydata/xarray/pull/2843  
263656773 MDExOlB1bGxSZXF1ZXN0MjYzNjU2Nzcz 2844 closed 0 Read grid mapping and bounds as coords DWesl 22566757 <!-- Feel free to remove check-list items aren't relevant to your change --> I prefer having these as coordinates rather than data variables. This does not cooperate with slicing/pulling out individual variables. `grid_mapping` should only be associated with variables that have horizontal dimensions or coordinates. `bounds` should stay associated despite having more dimensions. I have not implemented similar functionality for the iris conversions. An alternate approach to dealing with bounds (not used here) is to use a `pandas.IntervalIndex` http://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.IntervalIndex.html#pandas.IntervalIndex and use where the coordinate is within its cell to determine on which side the intervals are closed (`x_dim == x_dim_bnds[:, 0]` corresponds to "left", `x_dim == x_dim_bnds[:, 1]` corresponds to "right", and anything else is "neither"). This would stay through slicing and might already be used for `.groupby_bins()`, but would not generalize to boundaries of multidimensional coordinates unless someone implements a multidimensional generalization of `pd.IntervalIndex` - [ ] Closes #xxxx - [X] Tests added - [ ] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API 2019-03-22T15:25:37Z 2021-02-17T16:35:56Z 2021-02-17T16:35:56Z 2021-02-17T16:35:56Z 12b4480ff2bde696142ca850275cdcc85ca0fbc9     0 d3ec7abca84e0cdbdfbd07b7465b208af6ccb262 10f0227a1667c5ab3c88465ff1572065322cde77 CONTRIBUTOR   xarray 13221727 https://github.com/pydata/xarray/pull/2844  

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CREATE TABLE [pull_requests] (
   [id] INTEGER PRIMARY KEY,
   [node_id] TEXT,
   [number] INTEGER,
   [state] TEXT,
   [locked] INTEGER,
   [title] TEXT,
   [user] INTEGER REFERENCES [users]([id]),
   [body] TEXT,
   [created_at] TEXT,
   [updated_at] TEXT,
   [closed_at] TEXT,
   [merged_at] TEXT,
   [merge_commit_sha] TEXT,
   [assignee] INTEGER REFERENCES [users]([id]),
   [milestone] INTEGER REFERENCES [milestones]([id]),
   [draft] INTEGER,
   [head] TEXT,
   [base] TEXT,
   [author_association] TEXT,
   [auto_merge] TEXT,
   [repo] INTEGER REFERENCES [repos]([id]),
   [url] TEXT,
   [merged_by] INTEGER REFERENCES [users]([id])
);
CREATE INDEX [idx_pull_requests_merged_by]
    ON [pull_requests] ([merged_by]);
CREATE INDEX [idx_pull_requests_repo]
    ON [pull_requests] ([repo]);
CREATE INDEX [idx_pull_requests_milestone]
    ON [pull_requests] ([milestone]);
CREATE INDEX [idx_pull_requests_assignee]
    ON [pull_requests] ([assignee]);
CREATE INDEX [idx_pull_requests_user]
    ON [pull_requests] ([user]);