pull_requests
18 rows where milestone = 836999
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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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21565728 | MDExOlB1bGxSZXF1ZXN0MjE1NjU3Mjg= | 236 | closed | 0 | WIP: convert to/from cdms2 variables | shoyer 1217238 | Fixes #133 @DamienIrving am I missing anything obvious here? | 2014-09-22T08:48:52Z | 2014-12-19T09:11:42Z | 2014-12-19T09:11:39Z | 2014-12-19T09:11:39Z | d1099053c9ebbb1169f72fb301913899453fd5ef | 0.3.2 836999 | 0 | 784e24435c2cfddc3cdaab1866d2d8d7ee8eadd5 | 731a0e2b20fac802a6ce7899b1bb3ba14eb3cad0 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/236 | |||
23436973 | MDExOlB1bGxSZXF1ZXN0MjM0MzY5NzM= | 269 | closed | 0 | Fixes for dtype casting | shoyer 1217238 | Fixes #264 Fixes #259 (casting of masked arrays) | 2014-10-28T06:37:55Z | 2014-10-28T06:47:50Z | 2014-10-28T06:47:38Z | 2014-10-28T06:47:38Z | 9d4bef67bfa3108f605912a5e3a01b821f6a2ab4 | 0.3.2 836999 | 0 | 6eacd47b9575fb44792f225494834497e1c7978c | ee1369f72f20dad6331aa96710cc9f3237b195ec | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/269 | |||
23559561 | MDExOlB1bGxSZXF1ZXN0MjM1NTk1NjE= | 270 | closed | 0 | Fix guess_time_units if NaT is present | shoyer 1217238 | 2014-10-29T19:54:05Z | 2014-10-29T20:09:18Z | 2014-10-29T20:07:02Z | 2014-10-29T20:07:02Z | 6a2966925b4cfde53c8d9182156fab1f0c97070b | 0.3.2 836999 | 0 | 5c8a89ff4e781e22c3a1ef3f97564d71819e912f | 4e06b33fd9e2848caae50ca48c126a749bf2d9a5 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/270 | ||||
23575223 | MDExOlB1bGxSZXF1ZXN0MjM1NzUyMjM= | 271 | closed | 0 | Add backends integration test for roundtripping datetime arrays | shoyer 1217238 | Not sure how we missed this before. Also includes a fix for writing datetime arrays with missing values. | 2014-10-30T00:19:58Z | 2014-10-30T02:32:23Z | 2014-10-30T02:32:21Z | 2014-10-30T02:32:21Z | faa1de8ebcd6a20348c86df717dfd0bda2f019c7 | 0.3.2 836999 | 0 | 4e31557f9a55af9926c0bd14b9426728c8ae25d9 | fdb4d455937636bb3d1722b78009b23341b77f78 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/271 | |||
25319567 | MDExOlB1bGxSZXF1ZXN0MjUzMTk1Njc= | 282 | closed | 0 | Serialize non-index coordinates to netCDF files | shoyer 1217238 | Fixes #231 This PR ensures non-index coordinates can be roundtripped to netCDF and back by using the CF convention of the 'coordinates' attribute on a "data variable". In cases where there are no data variables available, we fall back to the (extended, non-CF) convention of saving 'coordinates' as a global attribute. I also added the `xray.decode_cf` function to the API. This function can decode either datasets or datastores into decoded datasets, which is handy, for example, if a dataset is serialized according to CF conventions but already in memory (e.g., saved in JSON). @akleeman: I could use some guidance from you on want to do about `test_roundtrip_coordinates` on `TestCFEncodedDataStore`. I am tentatively skipping it, but it would be nice to get it working. To do so will require some tweaks to the API for the `Datastore.load` method. | 2014-12-02T05:11:23Z | 2014-12-07T02:44:14Z | 2014-12-07T02:44:11Z | 2014-12-07T02:44:11Z | 8b25628a5cad01444dc957c44399bcbcc577af18 | 0.3.2 836999 | 0 | e1000d680cc9fee011ec0eff29b3ae2f9017d7f9 | a5837164f80a4bffcfda52a3edcc4f40c947d336 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/282 | |||
25547586 | MDExOlB1bGxSZXF1ZXN0MjU1NDc1ODY= | 285 | closed | 0 | Fix to_netcdf with 0d sting variables | shoyer 1217238 | Fixes #284 | 2014-12-05T03:29:54Z | 2014-12-05T03:57:18Z | 2014-12-05T03:57:16Z | 2014-12-05T03:57:16Z | 353d1bf952659ef188568a7a9d490c29882b34d7 | 0.3.2 836999 | 0 | f8022ac535c4854c9d123ef39f1dab74f1c8edba | a5837164f80a4bffcfda52a3edcc4f40c947d336 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/285 | |||
25627557 | MDExOlB1bGxSZXF1ZXN0MjU2Mjc1NTc= | 287 | closed | 0 | Fixes for Dataset.to_dataframe() | shoyer 1217238 | Fixes #278 | 2014-12-07T03:24:55Z | 2014-12-07T06:22:51Z | 2014-12-07T06:22:47Z | 2014-12-07T06:22:47Z | 94033ffe16a48f7ad15ed91b66735a05bc5be5e8 | 0.3.2 836999 | 0 | 69ea1a09b90614242adca4314f827f437bbefb4b | b9b9b9c984c2ea0d796f6d6d45e15a63d32b5926 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/287 | |||
25630036 | MDExOlB1bGxSZXF1ZXN0MjU2MzAwMzY= | 288 | closed | 0 | Add optional dependency on cyordereddict | shoyer 1217238 | This makes indexing a dataset (`ds['foo']`) about 30% faster in cases where `cyordereddict` is available. | 2014-12-07T09:15:35Z | 2014-12-07T09:53:51Z | 2014-12-07T09:53:49Z | 2014-12-07T09:53:49Z | 8c2715459fb7fa991a2c3fa167c6d9ae4d073b73 | 0.3.2 836999 | 0 | 07823e96533e2dc6c870d3a372e2ee283f7312d5 | 2a8f1860d93ea9e2635044ad44dc859c67a6ac90 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/288 | |||
25798861 | MDExOlB1bGxSZXF1ZXN0MjU3OTg4NjE= | 289 | closed | 0 | Faster path for Dataset/DataArray indexing | shoyer 1217238 | My benchmark shows this commit makes things about 35% faster for positional indexing. | 2014-12-10T04:48:31Z | 2014-12-10T04:53:17Z | 2014-12-10T04:53:15Z | 2014-12-10T04:53:15Z | fe1ce8fbc4aa366e37ab6d72b04914359f581528 | 0.3.2 836999 | 0 | a5528b44a95f4973ebe6546b1f143da1c8c19886 | 8e56736a87e53322c5bd8e3e20cf92ec352548f2 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/289 | |||
25802877 | MDExOlB1bGxSZXF1ZXN0MjU4MDI4Nzc= | 291 | closed | 0 | Support using dictionaries for labeled indexing | shoyer 1217238 | Fixes #187 As of this change, you can use dictionaries for indexing along a dimension, e.g., in the form `array.loc[dict(x='2000-01-01')]` or `array[dict(x=0)]`. In particular, you can use this for _assignment_, not just for selecting values (e.g., `array[dict(x=0)] = 0`). It was previously difficult to do assignment with labeled dimensions in xray. | 2014-12-10T07:14:47Z | 2014-12-11T22:28:26Z | 2014-12-11T22:28:19Z | 2014-12-11T22:28:19Z | 4564915e1fdf08baed1def669d8f453393aae66a | 0.3.2 836999 | 0 | 967809a1217694a31fd9b3c918ecb2bea20b5411 | 412215858a6c14b1354bf1a7c91c0177189a06c2 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/291 | |||
25958168 | MDExOlB1bGxSZXF1ZXN0MjU5NTgxNjg= | 292 | closed | 0 | Allow for pd.TimedeltaIndex and serialize it to netCDF | shoyer 1217238 | Fixes #55 | 2014-12-12T08:19:32Z | 2014-12-12T09:41:03Z | 2014-12-12T09:41:01Z | 2014-12-12T09:41:01Z | 81bbf9ef2643303d3e595a1d090c4610e7aa3416 | 0.3.2 836999 | 0 | 2eee7df09dd0888569497ac227b969c8ba1faa21 | a31e0e5f85336aa9da87dacf93e765007b3a60cb | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/292 | |||
26349640 | MDExOlB1bGxSZXF1ZXN0MjYzNDk2NDA= | 294 | closed | 0 | Coerce arrays of datetime.datetime objects into datetime64 | shoyer 1217238 | Fixes #136 Also includes some speedups for Variable construction | 2014-12-19T03:39:35Z | 2014-12-19T05:27:51Z | 2014-12-19T05:27:50Z | 2014-12-19T05:27:50Z | dbf5fd51845c0510422243fbcfb5a374c3243470 | 0.3.2 836999 | 0 | 3925fda821688b8d824b277b0d82798e83dc40e6 | a9f63ffbee4bc929c29d682c3a119db10d11c78e | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/294 | |||
26355014 | MDExOlB1bGxSZXF1ZXN0MjYzNTUwMTQ= | 295 | closed | 0 | Cleanup & bug fix | shoyer 1217238 | Fixes #279. | 2014-12-19T07:17:35Z | 2014-12-19T07:21:33Z | 2014-12-19T07:21:31Z | 2014-12-19T07:21:31Z | 3bdb8b84ea79a23ca73162aa67880e0ed4fd8d27 | 0.3.2 836999 | 0 | 889d80332d34b597070ee32211475266e2e86c9f | 0c7e1b168e05052a0bfcabb16588dec6aba6d9bf | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/295 | |||
26410800 | MDExOlB1bGxSZXF1ZXN0MjY0MTA4MDA= | 296 | closed | 0 | BUG: fix string <-> char conversion for non-contiguous arrays | shoyer 1217238 | 2014-12-20T02:23:57Z | 2014-12-20T02:44:03Z | 2014-12-20T02:44:01Z | 2014-12-20T02:44:01Z | b93a1de8621879bca62e4ea86c2634d6db63fc44 | 0.3.2 836999 | 0 | 543fa95e22e89be45c5c712feaa3dd2a5cb7334b | ad6d6a1f0c9c2558e0388041a351914ce4f08bd2 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/296 | ||||
26443413 | MDExOlB1bGxSZXF1ZXN0MjY0NDM0MTM= | 297 | closed | 0 | Better decoding of netCDF times | shoyer 1217238 | This version avoids using the netCDF4 library unless strictly necessary (e.g., for non-standard calendars). | 2014-12-22T08:03:02Z | 2014-12-22T20:09:43Z | 2014-12-22T20:09:41Z | 2014-12-22T20:09:41Z | 83aa2c13cfe17e0a5b64314aa85ee2cf4e9529f7 | 0.3.2 836999 | 0 | 14466e68f1ccdbaf428833aec04d8067379365a4 | 5ac8205d4d6475b6244ebd569b7e7beae1ca7b66 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/297 | |||
26443536 | MDExOlB1bGxSZXF1ZXN0MjY0NDM1MzY= | 298 | closed | 0 | Fix DataArray.__init__ docstring | shoyer 1217238 | xref: #277 | 2014-12-22T08:07:10Z | 2014-12-22T08:25:15Z | 2014-12-22T08:25:15Z | 2014-12-22T08:25:15Z | 57814c8dd2b192c42350337e9be78e3af1df54b7 | 0.3.2 836999 | 0 | 5797d2eb93dab82891b3e3aae607f7245dd3cfa2 | 5ac8205d4d6475b6244ebd569b7e7beae1ca7b66 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/298 | |||
26477924 | MDExOlB1bGxSZXF1ZXN0MjY0Nzc5MjQ= | 299 | closed | 0 | Update docs | shoyer 1217238 | 2014-12-22T20:09:54Z | 2014-12-22T21:00:58Z | 2014-12-22T21:00:56Z | 2014-12-22T21:00:56Z | d167c84f0f696a87423acbb7897035f32f0fdcc1 | 0.3.2 836999 | 0 | 20c66b3dbd1481f7e1e09cdd46603cd321c4717b | 013bbabfc0b3ac7606d4102efe231996c6c65da8 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/299 | ||||
26546974 | MDExOlB1bGxSZXF1ZXN0MjY1NDY5NzQ= | 301 | closed | 0 | Add attribute style access for variables and attributes | shoyer 1217238 | Fixes #286 | 2014-12-24T06:41:22Z | 2014-12-24T07:07:25Z | 2014-12-24T07:07:24Z | 2014-12-24T07:07:24Z | 646579f51bf579608a76658f7882fe14ecda7ae8 | 0.3.2 836999 | 0 | 5092b3c51711ede11558f5524522b37972e1f2c3 | b1c8cdd46df56f1048c3606ef0f45ae3312ca2dd | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/301 |
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