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- cartesian product of coordinates and using it to index / fill empty dataset · 1 ✖
id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
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366825366 | https://github.com/pydata/xarray/issues/1914#issuecomment-366825366 | https://api.github.com/repos/pydata/xarray/issues/1914 | MDEyOklzc3VlQ29tbWVudDM2NjgyNTM2Ng== | fujiisoup 6815844 | 2018-02-19T23:21:05Z | 2018-02-19T23:34:58Z | MEMBER | I am not sure if it is efficient to interact with a cluster, but I often use In [2]: data1 = data.stack(xy=['x', 'y'])
...: data1
...:
Out[2]:
<xarray.DataArray (xy: 12)>
array([ nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan])
Coordinates:
* xy (xy) MultiIndex
- x (xy) int64 0 0 0 0 1 1 1 1 2 2 2 2
- y (xy) object 'a' 'b' 'c' 'd' 'a' 'b' 'c' 'd' 'a' 'b' 'c' 'd'
In [6]: data1 Out[6]: <xarray.DataArray (xy: 12)> array([ nan, nan, nan, nan, 2., nan, nan, nan, nan, nan, nan, nan]) Coordinates: * xy (xy) MultiIndex - x (xy) int64 0 0 0 0 1 1 1 1 2 2 2 2 - y (xy) object 'a' 'b' 'c' 'd' 'a' 'b' 'c' 'd' 'a' 'b' 'c' 'd' ``` Note that we need to access via EDIT: I modified my previous comment to take the partial assignment into accout. |
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cartesian product of coordinates and using it to index / fill empty dataset 297560256 |
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