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SparseSeries.array only returns non-fills

See original GitHub issue

Code Sample, a copy-pastable example if possible

>>> np.array(pd.SparseSeries([0, 1], fill_value=0))
array([1])

Expected Output

array([0, 1])

this should really be consistent with Series rather than just returning the non-fill values (i.e. rather than being equivalent to np.array(ps.SparseArray([np.nan, 1])).

output of `pd.show_versions()`

Pandas 0.18.1

should alone be relevant.

Apologies I’ve not checked if this is fixed in master. Just passing on issues from scikit-learn/scikit-learn#7352.

Issue Analytics

State:
Created 7 years ago
Reactions:1
Comments:17 (17 by maintainers)

Top GitHub Comments

1reaction

jrebackcommented, Jan 15, 2018

@hexgnu this is a bit more complicated here, __array__ can/should return a dense view of the data, but you can handle the wrapping/unwrapping to a SparseSeries thru things like __array_wrap__ (which are defined inSeries)

0reactions

TomAugspurgercommented, Oct 17, 2018

This was fixed by https://github.com/pandas-dev/pandas/pull/22325

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