pull_requests: 13333082
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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 |
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| 13333082 | MDExOlB1bGxSZXF1ZXN0MTMzMzMwODI= | 54 | closed | 0 | Internal refactor of XArray, with a new CoordXArray subtype | 1217238 | This allows us to simplify our internal model for XArray (it always cached internally as a base ndarray) and supports some previously tricky aspects involving pandas.Index objects. Noteably: 1. The dtype of arrays stored as pandas.Index objects can now be faithfully saved and restored. Doing math with XArray objects always yields objects with the right dtype, so `ds['latitude'] + 1` has dtype=float, not dtype=object. 2. It's no longer necessary to load index data into memory upon creating a new Dataset. Instead, the index data can be loaded on demand. 3. `var.data` is always an ndarray. `var.index` is always a pandas.Index. Related issues: #17, #39, #40. | 2014-03-07T22:42:35Z | 2014-03-24T07:21:02Z | 2014-03-11T01:01:40Z | 2014-03-11T01:01:40Z | 5a2db298c6203246ab647e8a1bd2d8fc62b56a3e | 0 | 8ea13703314ff1dcfb97526393ad92a1083fd54a | fdbfb7c2a5126221d404047190caa04a6229fb52 | MEMBER | 13221727 | https://github.com/pydata/xarray/pull/54 |
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