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  • Equivalent of numpy.insert for DataSet / DataArray? · 2 ✖

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  • NONE · 2 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
332619692 https://github.com/pydata/xarray/issues/1596#issuecomment-332619692 https://api.github.com/repos/pydata/xarray/issues/1596 MDEyOklzc3VlQ29tbWVudDMzMjYxOTY5Mg== darothen 4992424 2017-09-27T18:49:34Z 2017-09-27T18:49:34Z NONE

@willirath Never hurts! 

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   Equivalent of numpy.insert for DataSet / DataArray? 260912521
332519089 https://github.com/pydata/xarray/issues/1596#issuecomment-332519089 https://api.github.com/repos/pydata/xarray/issues/1596 MDEyOklzc3VlQ29tbWVudDMzMjUxOTA4OQ== darothen 4992424 2017-09-27T13:23:38Z 2017-09-27T13:23:38Z NONE

@willirath is your time data equally spaced? If so, you should be able to use the new version of DataArray.resample() available on the master (and scheduled for the 0.10.0 release) which supports upsampling/infilling.

Should work something like this, assuming each timestep is a daily value on the time axis:

``` python ds = xr.open_mfdataset("paths/to/my/data.nc")

ds_infilled = ds.resample(time='1D').asfreq() ```

That should get you nans wherever your data is missing.

 
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   Equivalent of numpy.insert for DataSet / DataArray? 260912521

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