issue_comments: 554581481
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| html_url | issue_url | id | node_id | user | created_at | updated_at | author_association | body | reactions | performed_via_github_app | issue |
|---|---|---|---|---|---|---|---|---|---|---|---|
| https://github.com/pydata/xarray/issues/1739#issuecomment-554581481 | https://api.github.com/repos/pydata/xarray/issues/1739 | 554581481 | MDEyOklzc3VlQ29tbWVudDU1NDU4MTQ4MQ== | 5635139 | 2019-11-16T00:28:37Z | 2019-11-16T00:28:37Z | MEMBER | What do we think about attempting to enforce a dimension order throughout the dataset? That would solve these issues for free. We already have some order in (Maybe this doesn't need to be strictly enforced, but we'd at least set the expectation that dimensions could be reordered to that dimension order at any time) Or are there uses to having different dimension order throughout a dataset? ```python In [45]: ds Out[45]: <xarray.Dataset> Dimensions: (lat: 25, lon: 53, time: 2920) Coordinates: * lat (lat) float32 75.0 72.5 70.0 67.5 65.0 ... 25.0 22.5 20.0 17.5 15.0 * lon (lon) float32 200.0 202.5 205.0 207.5 ... 322.5 325.0 327.5 330.0 * time (time) datetime64[ns] 2013-01-01 ... 2014-12-31T18:00:00 Data variables: air (time, lat, lon) float32 ... Attributes: Conventions: COARDS title: 4x daily NMC reanalysis (1948) description: Data is from NMC initialized reanalysis\n(4x/day). These a... platform: Model references: http://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanaly... In [46]: ds.dims Out[46]: Frozen(SortedKeysDict({'lat': 25, 'time': 2920, 'lon': 53})) In [47]: ds.sizes Out[47]: Frozen(SortedKeysDict({'lat': 25, 'time': 2920, 'lon': 53})) ``` |
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