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  • maahn · 1 ✖

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  • DataArray.unstack taking unreasonable amounts of memory · 1 ✖

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id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
411815694 https://github.com/pydata/xarray/issues/1560#issuecomment-411815694 https://api.github.com/repos/pydata/xarray/issues/1560 MDEyOklzc3VlQ29tbWVudDQxMTgxNTY5NA== maahn 222557 2018-08-09T16:21:41Z 2018-08-09T16:21:41Z NONE

What about a quick fix with index.equals like this (without the prints of course): https://github.com/maahn/xarray/commit/cf83991a161fbd89af2029a69cb50f1e09a5ed45. For the example above 

arr = xr.DataArray(np.empty([1, 8996, 9223]))
arr = arr.stack(flat_dim=['dim_1', 'dim_2'])
%time arr.unstack('flat_dim')

the modified routine takes 5.75 s in comparison to 6min 40s with xr 0.10.7 and pd 0.23.3. Not sure whether this is related to a newer version, but index.equals(full_idx) takes actually only 2e-4 s in that example. When slicing or reordering is applied to the MultiIndex

arr = xr.DataArray(np.arange(20).reshape((1, 10, 2))).stack(flat_dim=['dim_1', 'dim_2'])
arr.isel(flat_dim = [1,2]).unstack('flat_dim')

or

arr = xr.DataArray(np.arange(20).reshape((1, 10, 2))).stack(flat_dim=['dim_1', 'dim_2'])
arr[:,::-1].unstack('flat_dim')

it will fall back to the old method with reindex. 

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   DataArray.unstack taking unreasonable amounts of memory 255989233

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