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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
26657336 MDExOlB1bGxSZXF1ZXN0MjY2NTczMzY= 302 closed 0 Variables no longer conflict if they are broadcast equal and rather are promoted to use common dimensions shoyer 1217238 Fixes #243. The idea here is that variables should not conflict if they are equal after being broadcast against each other; rather variables should be promoted to the common dimensions. This should resolve a number of annoyances causes by mixing scalar and non-scalar variables. This PR includes fixes for `concat`, `Dataset.merge` (and thus `Dataset.update` and `Dataset.__setitem__`) and `Dataset`/`DataArray` arithmetic (via `Coordinates.merge`). 2014-12-29T19:19:42Z 2014-12-29T19:53:14Z 2014-12-29T19:52:57Z 2014-12-29T19:52:57Z 71d8f38d6a179860afcf9dc2243bb424e6f9a0c2   0.4 799013 0 d876417ad7ad44e7d0d18ffcaa3df7e281c23db2 fb9a5dbfbc9e0585f8ee14af42d1fa41d86ef9d7 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/302  
26786572 MDExOlB1bGxSZXF1ZXN0MjY3ODY1NzI= 304 closed 0 Switch to use nan-skipping aggregation functions by default and add .median() method shoyer 1217238 TODO: - ~~update documentation~~ (I'll do this later) - ~~update minimum required numpy version to 1.9? (so we can use np.nanmedian)~~ (added an informative error message for median) fixes #209 xref #130 2015-01-03T20:19:26Z 2015-01-04T16:05:30Z 2015-01-04T16:05:28Z 2015-01-04T16:05:28Z 1c61b5007ed78b9d99a4ab06e724c9244acc46d7   0.4 799013 0 bf299aa6f94833172784652173e91bd7b0ea7814 9ead00b42399b4dbba93b9559bdee6548a5436b8 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/304  
26973957 MDExOlB1bGxSZXF1ZXN0MjY5NzM5NTc= 306 closed 0 Fix coercion of numeric strings to objects shoyer 1217238 Fixes #305 2015-01-07T17:45:23Z 2015-02-23T06:09:10Z 2015-01-07T18:14:31Z 2015-01-07T18:14:31Z c5805324eafa2804ce3066acb4cbc0577c6548b7   0.4 799013 0 329c7f193344d19bf2938fc37acca5fad6396755 2ba9c321aee791a98f63b2dd17decc8ffb665bea MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/306  
27010288 MDExOlB1bGxSZXF1ZXN0MjcwMTAyODg= 307 closed 0 Skip NA in groupby groups shoyer 1217238 This makes xray consistent with the behavior of pandas. 2015-01-08T06:40:17Z 2015-01-08T06:51:12Z 2015-01-08T06:51:10Z 2015-01-08T06:51:10Z c7a943335b0b1ac1305ef4e2a85ad915e9d8017c   0.4 799013 0 b8bfc9b1c3d098037a4071fb1bd12d70aaf527b1 546d24049357fc04e995d3ff70344698acf81c1e MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/307  
27171205 MDExOlB1bGxSZXF1ZXN0MjcxNzEyMDU= 309 closed 0 Fix typos in docs eriknw 2058401   2015-01-12T01:00:09Z 2015-01-12T01:44:11Z 2015-01-12T01:43:43Z 2015-01-12T01:43:43Z 0cba0f12b8b8c805d26cb242d134485648d5d021   0.4 799013 0 3d216be4eb9e7510b10bc00c18c23dea43026edb 19df8d202b1d8054019e7e42365c67cdde6ff448 CONTRIBUTOR   xarray 13221727 https://github.com/pydata/xarray/pull/309  
27392995 MDExOlB1bGxSZXF1ZXN0MjczOTI5OTU= 310 closed 0 More robust CF datetime unit parsing akleeman 514053 This makes it possible to read datasets that don't follow CF datetime conventions perfectly, such as the following example which (surprisingly) comes from NCEP/NCAR (you'd think they would follow CF!) ``` ds = xray.open_dataset('http://thredds.ucar.edu/thredds/dodsC/grib/NCEP/GEFS/Global_1p0deg_Ensemble/members/GEFS_Global_1p0deg_Ensemble_20150114_1200.grib2/GC') print ds['time'].encoding['units'] u'Hour since 2015-01-14T12:00:00Z' ``` 2015-01-14T23:19:07Z 2015-01-14T23:36:34Z 2015-01-14T23:35:27Z 2015-01-14T23:35:27Z 96f2c394961b37f6e1238539bb254259c543b8ff shoyer 1217238 0.4 799013 0 d5115cb1947b0679cc9998665a71f5d85e260623 4a4be4ace8f42dbc7c4ab016ab58a46812b37ad1 CONTRIBUTOR   xarray 13221727 https://github.com/pydata/xarray/pull/310  
27728932 MDExOlB1bGxSZXF1ZXN0Mjc3Mjg5MzI= 311 closed 0 Bug fix for DataArray.to_dataframe with coords with different dimensions shoyer 1217238   2015-01-21T01:40:06Z 2015-01-21T01:44:29Z 2015-01-21T01:44:28Z 2015-01-21T01:44:28Z 42ee237d34f3054181eebab41bf5f06b3a16882b   0.4 799013 0 afb658fad24a43edcb42ce76a5551c905c1a6baf 575a7117179ce9e0c6c1b928445aeaead5e808d1 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/311  
28612773 MDExOlB1bGxSZXF1ZXN0Mjg2MTI3NzM= 312 closed 0 BUG: Fix slicing with negative step size shoyer 1217238 As identified here: https://github.com/perrette/dimarray/commit/ad4ab4d049f49881b28120d276337b2cab5e4061 2015-02-04T04:32:07Z 2015-02-04T04:34:46Z 2015-02-04T04:34:39Z 2015-02-04T04:34:39Z 288b83ebba811c8f87868859369ba693624d44a3   0.4 799013 0 6a62642298b1bce93ec444f92cd54ffc37ea193e 299404da3f3be5b562baf350fb178cf9d0b99c63 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/312  
28617914 MDExOlB1bGxSZXF1ZXN0Mjg2MTc5MTQ= 313 closed 0 Fix decoding missing coordinates shoyer 1217238 Fixes #308 2015-02-04T07:19:01Z 2015-02-04T07:21:03Z 2015-02-04T07:21:01Z 2015-02-04T07:21:01Z 61f33f06eaf53b6aabbf509b664414a546ace672   0.4 799013 0 ed4492a39d42752e708c726e2b578a7a449da807 2efda08952b80b43dfcac07dc2b5ae6fff468561 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/313  
28783997 MDExOlB1bGxSZXF1ZXN0Mjg3ODM5OTc= 315 closed 0 Bug fix for multidimensional reindex edge case shoyer 1217238   2015-02-06T04:09:09Z 2015-02-06T04:10:23Z 2015-02-06T04:10:21Z 2015-02-06T04:10:21Z d3aaa5558481a17f2b7631a07aace14d875a05c8   0.4 799013 0 48a004de46fe72e92145109c08b08512dab1c34c 2d954c45b03c3571c2cbf907543bad78e2cd8fbd MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/315  
29021638 MDExOlB1bGxSZXF1ZXN0MjkwMjE2Mzg= 317 closed 0 Fall back to netCDF4 if pandas can’t parse a date sjpfenninger 141709 Addresses #316 2015-02-10T16:31:34Z 2016-04-01T14:23:10Z 2015-02-10T18:37:32Z 2015-02-10T18:37:32Z 6d270b42920ecb46a1f296ceb5705d58edfb175f   0.4 799013 0 b68b03c3b7a2e666f76d96fabd659dd78c5bd693 8f7fc86e014ca38af880476e1467d0b8236ef2e8 CONTRIBUTOR   xarray 13221727 https://github.com/pydata/xarray/pull/317  
29033210 MDExOlB1bGxSZXF1ZXN0MjkwMzMyMTA= 318 closed 0 Fix DataArray.loc indexing with Ellipsis: da.loc[...] shoyer 1217238   2015-02-10T18:46:37Z 2015-02-10T18:59:32Z 2015-02-10T18:59:31Z 2015-02-10T18:59:31Z f24994982b98c546657178d536978bbd46c91d43   0.4 799013 0 2a49692917c0368143e145038bb1d7b2ff3b34e8 14de7b991cc136ab932a2fd9ef4ce0a1ef77eea4 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/318  
29250720 MDExOlB1bGxSZXF1ZXN0MjkyNTA3MjA= 321 closed 0 Automatic label-based alignment for math and Dataset constructor shoyer 1217238 Fixes #186. This will be a major breaking change for v0.4. For example, we can now do things like this: ``` In [5]: x = xray.DataArray(range(5), dims='x') In [6]: x Out[6]: <xray.DataArray (x: 5)> array([0, 1, 2, 3, 4]) Coordinates: * x (x) int64 0 1 2 3 4 In [7]: x[:4] + x[1:] Out[7]: <xray.DataArray (x: 3)> array([2, 4, 6]) Coordinates: * x (x) int64 1 2 3 ``` 2015-02-13T09:31:43Z 2015-03-03T06:24:02Z 2015-02-13T22:19:29Z 2015-02-13T22:19:29Z b3bb2ebeeb9466d9ed2f7c41865b6c6105a10e01   0.4 799013 0 6ccf629511dce9ef3fb6074fe2133d3277b506da 2eb0d96fc9884e8d6355524d5b8eb972f3bdf0b3 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/321  
29500687 MDExOlB1bGxSZXF1ZXN0Mjk1MDA2ODc= 322 closed 0 Support reindexing with an optional fill method shoyer 1217238 e.g., pad, backfill or nearest 2015-02-18T04:32:47Z 2015-02-18T04:42:00Z 2015-02-18T04:41:59Z 2015-02-18T04:41:59Z 824bdcccba8226e3dd50dcf38fe26e3771751fd0   0.4 799013 0 f57a6c825113e0f6480afa88cee012ba17da5f2d 9fbd15d66b54e8ed7cf5e21a1202c8d69777e031 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/322  
29595225 MDExOlB1bGxSZXF1ZXN0Mjk1OTUyMjU= 325 closed 0 Rename Dataset.vars -> data_vars and remove deprecated aliases shoyer 1217238 Fixes #293 2015-02-19T09:01:45Z 2015-02-19T19:31:17Z 2015-02-19T19:31:11Z 2015-02-19T19:31:11Z 5aba479e0294f72ef734f223d3d810ff90d73ff4   0.4 799013 0 fcdbc7901e453740f4d96f4ee6bd905e91444e54 0cc5e23c170ab1bce471b1f3d2e44bea681c32f9 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/325  
29671328 MDExOlB1bGxSZXF1ZXN0Mjk2NzEzMjg= 327 closed 0 Cleanly apply generic ndarrays to DataArray.groupby IamJeffG 2002703 This is special cased for np.ndarrays: applying to DataArrays is not only inefficient but would also be wrong if the applied function wanted to change metadata. Fixes #326 2015-02-20T03:47:15Z 2015-02-20T04:41:10Z 2015-02-20T04:41:08Z 2015-02-20T04:41:08Z 13cdb1eb4ac2f7b8ad88be705005dead93ef8356   0.4 799013 0 57ea69c8988baf3d12ac3775e762ff45bed7ee71 3e3c84203c3f20515bb8d21ec72e9dcc0e2a568b CONTRIBUTOR   xarray 13221727 https://github.com/pydata/xarray/pull/327  
29759819 MDExOlB1bGxSZXF1ZXN0Mjk3NTk4MTk= 329 closed 0 Dataset.apply works if func returns like-shaped ndarrays shoyer 1217238 This extends the recent change by @IamJeffG (#327). 2015-02-21T20:54:00Z 2015-02-23T00:35:25Z 2015-02-23T00:35:23Z 2015-02-23T00:35:23Z 0fcefec07391a9b5fd8d4559fe7c01d624456c59   0.4 799013 0 602a2101d2d832d94e81b5aed3e2bbbe2e24d3eb 3309f62d7a80bfb8c8aa843a7fbbad546087435d MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/329  
29783867 MDExOlB1bGxSZXF1ZXN0Mjk3ODM4Njc= 330 closed 0 Improved error handling for datetime decoding errors shoyer 1217238 Fixes #323 We now get an error message with a lovely traceback when opening a dataset with invalid time units. For example: ``` Traceback (most recent call last): File "/Users/shoyer/dev/xray/xray/test/test_conventions.py", line 340, in test_invalid_units_raises_eagerly decode_cf(ds) File "/Users/shoyer/dev/xray/xray/conventions.py", line 775, in decode_cf decode_coords) File "/Users/shoyer/dev/xray/xray/conventions.py", line 716, in decode_cf_variables decode_times=decode_times) File "/Users/shoyer/dev/xray/xray/conventions.py", line 676, in decode_cf_variable data = DecodedCFDatetimeArray(data, units, calendar) File "/Users/shoyer/dev/xray/xray/conventions.py", line 340, in __init__ raise ValueError(msg) ValueError: unable to decode time units 'foobar since 123' with the default calendar. Try opening your dataset with decode_times=False. Full traceback: Traceback (most recent call last): File "/Users/shoyer/dev/xray/xray/conventions.py", line 331, in __init__ decode_cf_datetime(example_value, units, calendar) File "/Users/shoyer/dev/xray/xray/conventions.py", line 130, in decode_cf_datetime delta = _netcdf_to_numpy_timeunit(delta) File "/Users/shoyer/dev/xray/xray/conventions.py", line 72, in _netcdf_to_numpy_timeunit return {'seconds': 's', 'minutes': 'm', 'hours': 'h', 'days': 'D'}[units] KeyError: 'foobars' ``` Also includes a fix for a datetime decoding issue reported on the mailing list: https://groups.google.com/forum/#!topic/xray-dev/Sscsw5dQAqQ 2015-02-23T03:08:40Z 2015-02-25T22:00:36Z 2015-02-23T03:11:03Z 2015-02-23T03:11:03Z bb0ea831d39f861ab41767681078f90f73e50664   0.4 799013 0 ad346cea7831c6f53215ef60c28d7c17d1860e1d e82835013595795c50656bc66b586b751227c204 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/330  
29787573 MDExOlB1bGxSZXF1ZXN0Mjk3ODc1NzM= 331 closed 0 Documentation updates anticipating v0.4 shoyer 1217238   2015-02-23T05:51:42Z 2015-02-23T06:18:39Z 2015-02-23T06:18:35Z 2015-02-23T06:18:35Z 18fd604faf636f7836886029eac3323c73f37552   0.4 799013 0 a8bec91dd56f7c29753eefe56a060ee2b5f70065 102ade4ba851f5d6e0e40b6e2777bccacbc9b490 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/331  
29837685 MDExOlB1bGxSZXF1ZXN0Mjk4Mzc2ODU= 332 closed 0 Update time.season to use text labels like 'DJF' shoyer 1217238 Previously, I used numbers 1 through 4 for the sake of consistency with pandas, but such labels really were impossible to keep track of. 2015-02-23T19:31:58Z 2015-02-23T19:43:41Z 2015-02-23T19:43:39Z 2015-02-23T19:43:39Z a1f8e398dc4a6132c0ceeed5049afaf33944b162   0.4 799013 0 4f53c31e681fb2835886bc8a250ba0498c257d4d ea907af0ca5b8ee7c63b77581705827cd229ba55 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/332  
29863225 MDExOlB1bGxSZXF1ZXN0Mjk4NjMyMjU= 333 closed 0 Unify netCDF4 and scipy backends in the public API shoyer 1217238 Fixes #273 and half of #272 To serialize a dataset to a string/bytes, simply use `ds.to_netcdf()`. This behavior copies `DataFrame.to_csv()` from pandas. The legacy `dump` and `dumps` methods are deprecated. My main concern is that the default "format" option is depends on what dependencies the user has installed or if they are saving a file. That seems non-ideal, but may perhaps be the most pragmatic choice given the limitations of the netCDF4 format. This change also adds: - Support for writing datasets to a particular NETCDF4 group - Support for opening netCDF3 files from disk even without netCDF4-python if scipy is installed. CC @akleeman 2015-02-24T01:20:01Z 2015-02-25T06:21:03Z 2015-02-25T06:21:01Z 2015-02-25T06:21:01Z a26cbb42e41a0470394ff986093d1beffe18baf5   0.4 799013 0 b624603c93a77cf024f7dfae893b55154f9741d7 400317e9afbbfafacb3aea4ffd70e8790c936ee6 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/333  
29864970 MDExOlB1bGxSZXF1ZXN0Mjk4NjQ5NzA= 334 closed 0 Fix bug associated with reading / writing of mixed endian data. akleeman 514053 The right solution to this is to figure out how to successfully round trip endian-ness, but that seems to be a deeper issue inside netCDF4 (https://github.com/Unidata/netcdf4-python/issues/346) Instead we force all data to little endian before netCDF4 write. 2015-02-24T01:57:43Z 2015-02-26T04:45:18Z 2015-02-26T04:45:18Z   8634487c2196fc84708be8e49ce59213c7623dfc   0.4 799013 0 b2bec2f7a6e02b3994a8da47aa4845810baaf136 400317e9afbbfafacb3aea4ffd70e8790c936ee6 CONTRIBUTOR   xarray 13221727 https://github.com/pydata/xarray/pull/334  
29962836 MDExOlB1bGxSZXF1ZXN0Mjk5NjI4MzY= 335 closed 0 Add broadcast_equals method to Dataset and DataArray shoyer 1217238   2015-02-25T05:51:46Z 2015-02-26T04:35:52Z 2015-02-26T04:35:49Z 2015-02-26T04:35:49Z d97c28ee4962f59e7fe36d9c96a034cc67f1f484   0.4 799013 0 a066dc0346c4f9d40000f62f6ff1718725574152 400317e9afbbfafacb3aea4ffd70e8790c936ee6 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/335  
29964211 MDExOlB1bGxSZXF1ZXN0Mjk5NjQyMTE= 336 closed 0 Add Dataset.drop and DataArray.drop shoyer 1217238 These are convenient shortcuts for removing variables or index labels from an xray object. 2015-02-25T06:35:18Z 2015-02-25T22:01:49Z 2015-02-25T22:01:49Z 2015-02-25T22:01:49Z 78e563c864cd40cdc7f500f3ebb911eca58b2cf6   0.4 799013 0 903ad7088b53524e4120b577b37536bea8745114 b6baa768876891a9ee91bf7f4698b470f11dab25 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/336  
30056409 MDExOlB1bGxSZXF1ZXN0MzAwNTY0MDk= 337 closed 0 Cleanup (mostly documentation) shoyer 1217238   2015-02-26T07:40:01Z 2015-02-27T22:22:47Z 2015-02-26T07:43:37Z 2015-02-26T07:43:37Z 75ce04bf46d4a11d7920fa3b2a425c7d23ed7523   0.4 799013 0 ca14eb754bd04565866e9abbf31ccf03c62388c2 7ea9de85698ebe275868fc364886a5010d90f107 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/337  
30057152 MDExOlB1bGxSZXF1ZXN0MzAwNTcxNTI= 338 closed 0 Truncate long attributes when printing datasets shoyer 1217238 Only the first 500 characters are now shown, e.g., ``` In [2]: xray.Dataset(attrs={'foo': 'bar' * 1000}) Out[2]: <xray.Dataset> Dimensions: () Coordinates: *empty* Data variables: *empty* Attributes: foo: barbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarb arbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarba rbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarbar barbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarb arbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarba rbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarbar barbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarb arbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarbarba... ``` 2015-02-26T07:57:40Z 2015-02-26T08:06:17Z 2015-02-26T08:06:05Z 2015-02-26T08:06:05Z 4088a173e371f0047f9683d3c5473683a1c0b5cc   0.4 799013 0 5b8dbef12748fb1aecb00aa02982afcbd3bd3456 3eb015bb7a6d9dd1c51d5fd2e16c87afcee7c0a0 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/338  
30249875 MDExOlB1bGxSZXF1ZXN0MzAyNDk4NzU= 346 closed 0 Fix bug where Coordinates could turn Variable objects in Dataset constructor shoyer 1217238 This manifested itself in some variables not being written to netCDF files, because they were determined to be trivial indexes (hence that logic was also updated to be slightly less questionable). 2015-03-01T22:08:36Z 2015-03-01T23:57:58Z 2015-03-01T23:57:55Z 2015-03-01T23:57:55Z 239596f712c8adca92e72d19811122ae037b8790   0.4 799013 0 7c25a75ae5c076d11cc08efd18171bd7c6a9d641 ba560e16eb45ab23ddd5fd16e3b7f5dfdc3c8181 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/346  
30254961 MDExOlB1bGxSZXF1ZXN0MzAyNTQ5NjE= 348 closed 0 Fix Dataset aggregate boolean shoyer 1217238 Fixes #342 2015-03-02T02:26:27Z 2015-03-02T18:14:12Z 2015-03-02T18:14:11Z 2015-03-02T18:14:11Z 183fdd9d0168c7f65eb46dd27d8d89edb1fc928f   0.4 799013 0 947ed235386b5e7bca56ad87b846c832b900e9d4 3546b1ac11b93ff735c1690cb22ae1db31617201 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/348  
30310527 MDExOlB1bGxSZXF1ZXN0MzAzMTA1Mjc= 350 closed 0 Fix Dataset repr with netcdf4 datetime objects shoyer 1217238 Fixes #347 2015-03-02T19:06:28Z 2015-03-02T19:25:01Z 2015-03-02T19:25:00Z 2015-03-02T19:25:00Z 5c49411822b50fa5f7bb7d3e568e3d9ee914fb45   0.4 799013 0 a732934aac9d01d48aaedbcbb8314f290bcc198a 40476f6582473b8aaba3d6928fdfdd2c33a97f49 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/350  
30319637 MDExOlB1bGxSZXF1ZXN0MzAzMTk2Mzc= 351 closed 0 Switch the name of datetime components from 'time.month' to 'month' shoyer 1217238 Fixes #345 This lets you write things like: ``` counts = time.groupby('time.month').count() counts.sel(month=2) ``` instead of the previously valid ``` counts.sel(**{'time.month': 2}) ``` which is much more awkward. Note that this breaks existing code which relied on the old usage. CC @jhamman 2015-03-02T20:55:24Z 2015-03-02T23:20:09Z 2015-03-02T23:20:07Z 2015-03-02T23:20:07Z 157993f82a8d284203d13f400412659e4166f803   0.4 799013 0 918016b68bbd49ff7ccce081c48408c305940e40 2bbc41bf4bc459155abf59c7a9907cfdc79b1835 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/351  
30345380 MDExOlB1bGxSZXF1ZXN0MzAzNDUzODA= 355 closed 0 Partial fix for netCDF4 datetime issues shoyer 1217238 xref #340 2015-03-03T04:11:51Z 2015-03-03T05:02:54Z 2015-03-03T05:02:52Z 2015-03-03T05:02:52Z 511f79b1910e3f6bd1582c799ec1383d56d3f798   0.4 799013 0 32ba52b39e09e23e5fe9acc94e49427985cdea87 31b6365fe9f53c76eb31ec8be8a9e78006c84c35 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/355  
30348750 MDExOlB1bGxSZXF1ZXN0MzAzNDg3NTA= 356 closed 0 Documentation updates shoyer 1217238 Fixes #343 (among other small changes) 2015-03-03T06:01:03Z 2015-03-03T06:02:57Z 2015-03-03T06:02:56Z 2015-03-03T06:02:56Z bfd9aef74d2a9b43e810db631a3e459157640720   0.4 799013 0 5dd967c2ec4e978b3081134873922cef7ac0c811 37cb1d2d1e8968f5011e44d3e2bcfbc7ad29e055 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/356  

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