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id | node_id | number | title | user | state | locked | assignee | milestone | comments | created_at | updated_at ▲ | closed_at | author_association | active_lock_reason | draft | pull_request | body | reactions | performed_via_github_app | state_reason | repo | type |
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125708367 | MDU6SXNzdWUxMjU3MDgzNjc= | 712 | DataArrays should display their coordinates in the natural order | anntzer 1322974 | open | 0 | 13 | 2016-01-08T22:33:05Z | 2020-11-06T18:48:54Z | CONTRIBUTOR | Consider ``` from collections import * import numpy as np from xray import * d1 = DataArray(np.empty((2, 2)), coords=OrderedDict([("foo", [0, 1]), ("bar", [0, 1])])) d2 = DataArray(np.empty((2, 2)), coords=OrderedDict([("bar", [0, 1]), ("foo", [0, 1])])) ds = Dataset({"d1": d1, "d2": d2}) print(ds.d1) print(ds.d2) ``` This outputs
I understand that internally both DataArrays use the same coords object and thus the same coords order, but it would be helpful if, when printing d2 by itself, the coordinates were printed in the natural order ("bar", "foo"). In particular, when working interactively, the list of coordinates at the end of the repr is the most easy thing to spot, and thus most helpful to know how to format the call to |
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xarray 13221727 | issue | ||||||||
112254767 | MDU6SXNzdWUxMTIyNTQ3Njc= | 631 | Confusing error (or lack thereof) when coordinate and variable share the same name | anntzer 1322974 | open | 0 | 5 | 2015-10-19T23:39:22Z | 2019-04-19T15:39:55Z | CONTRIBUTOR | It probably makes sense to prevent dataset to have variables sharing the names of coordinates (what would
fails with
actually creates an empty dataset using
|
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xarray 13221727 | issue | ||||||||
112253425 | MDU6SXNzdWUxMTIyNTM0MjU= | 630 | Whether a DataArray is copied when inserted into a Dataset depends on whether coordinates match exactly | anntzer 1322974 | open | 0 | 16 | 2015-10-19T23:27:15Z | 2019-01-31T18:40:58Z | CONTRIBUTOR | Consider ``` import numpy as np from xray import * ds = Dataset({"a": DataArray(np.zeros((3, 4)))}) ds["b"] = b = DataArray(np.zeros((3, 4))) b[0, 0] = 1 print(ds["b"][0, 0]) # ==> prints 1 ds = Dataset({"a": DataArray(np.zeros((3, 4)))}) ds["b"] = b = DataArray(np.zeros((3, 3))) # !!! we implicitly fill the last column with nans. b[0, 0] = 1 print(ds["b"][0, 0]) # ==> prints 0 ``` In the first case, the dataset was modified when the dataarray was modified, but not in the second case. |
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xarray 13221727 | issue |
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