releases: 968974
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html_url | id | author | node_id | tag_name | target_commitish | name | draft | prerelease | created_at | published_at | body | reactions | mentions_count | repo |
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https://github.com/pydata/xarray/releases/tag/v0.3.2 | 968974 | 1217238 | MDc6UmVsZWFzZTk2ODk3NA== | v0.3.2 | main | 0 | 0 | 2014-12-24T07:48:03Z | 2015-02-19T19:39:32Z | This release focused on bug-fixes, speedups and resolving some niggling inconsistencies. There are a few cases where the behavior of xray differs from the previous version. However, I expect that in almost all cases your code will continue to run unmodified. xray now requires pandas v0.15.0 or later. This was necessary for supporting TimedeltaIndex without too many painful hacks. Backwards incompatible changes:
- Arrays of ``` In [1]: from datetime import datetime In [2]: xray.Dataset({'t': [datetime(2000, 1, 1)]})
Out[2]:
<xray.Dataset>
Dimensions: (t: 1)
Coordinates:
* t (t) datetime64[ns] 2000-01-01
Variables:
empty
Enhancements: - Due to popular demand, we have added experimental attribute style access as a shortcut for dataset variables, coordinates and attributes: ``` In [3]: ds = xray.Dataset({'tmin': ([], 25, {'units': 'celcius'})}) In [4]: ds.tmin.units Out[4]: 'celcius' ``` Tab-completion for these variables should work in editors such as IPython. However, setting variables or attributes in this fashion is not yet supported because there are some unresolved ambiguities. - You can now use a dictionary for indexing with labeled dimensions. This provides a safe way to do assignment with labeled dimensions: ``` In [5]: array = xray.DataArray(np.zeros(5), dims=['x']) In [6]: array[dict(x=slice(3))] = 1 In [7]: array
Out[7]:
<xray.DataArray (x: 5)>
array([ 1., 1., 1., 0., 0.])
Coordinates:
* x (x) int64 0 1 2 3 4
Bug fixes:
- Fix for |
13221727 |