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Allows for merging of SparseDataFrames, and fixes __array__ interface #19488

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Allows for merging of SparseDataFrames, and fixes __array__ interface #19488

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5b48613
Hrm I'm trying here but nothing seems to work
hexgnu Jan 26, 2018
555fb91
First pass at fixing issues with SparseDataFrame merging
hexgnu Feb 1, 2018
89677b0
Fix linting errors
hexgnu Feb 2, 2018
97bd19b
One more linting error
hexgnu Feb 2, 2018
b04ac64
Fixing more test failures
hexgnu Feb 2, 2018
d24e464
Add more tests and fix some existing ones
hexgnu Feb 2, 2018
a796280
Only allow for sparse merging if everything is sparse
hexgnu Feb 2, 2018
be09289
Some more tests
hexgnu Feb 2, 2018
1aef901
Merge remote-tracking branch 'upstream/master' into dense_array_sparse
hexgnu Feb 5, 2018
42680ba
Merge branch 'dense_array_sparse' into fix_for_merging_sparse_frames
hexgnu Feb 5, 2018
2084ed3
Fix problem with __array__ not showing dense values
hexgnu Feb 5, 2018
77c41b7
Fix some linting errors
hexgnu Feb 5, 2018
25fd08a
I think I fixed it
hexgnu Feb 5, 2018
cd583f7
Don't assume that the dtype is int64
hexgnu Feb 5, 2018
45e7cd3
Get rid of WTF from code
hexgnu Feb 5, 2018
6522d6b
Missed one point where assumed int64
hexgnu Feb 5, 2018
029d37b
Typo fix should be len(values.shape)
hexgnu Feb 5, 2018
730c152
This will fix windows bug on appveyor
hexgnu Feb 6, 2018
171f5dd
Linting error
hexgnu Feb 6, 2018
bde2588
Add whatsnew entry for everything
hexgnu Feb 6, 2018
bfe3065
Add docstring to is_sparse_join_units
hexgnu Feb 6, 2018
d13daa7
WIP for merging sparse frames
hexgnu Feb 7, 2018
3ddba8b
Merge remote-tracking branch 'upstream/master' into fix_for_merging_s…
hexgnu Feb 7, 2018
4fa7dec
Allow for indexes to where on SparseArray
hexgnu Feb 12, 2018
353171b
Rely on ABCSparseArray over SparseArray
hexgnu Feb 12, 2018
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Linting error
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@hexgnu
hexgnu committed Feb 6, 2018
commit 171f5dd309f2dec9681ae1e868b7b42e7de2d19c
3 changes: 2 additions & 1 deletion pandas/tests/reshape/merge/test_merge.py
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Expand Up @@ -1886,7 +1886,8 @@ def test_merge_dense_sparse_frames(self, fill_value, how):

for column in dense_merge.columns:
dense_col = merged[column].to_dense()
tm.assert_series_equal(dense_col, dense_merge[column], check_dtype=False)
tm.assert_series_equal(dense_col, dense_merge[column],
check_dtype=False)

to_merge = to_merge[::-1]
to_merge_dense = to_merge_dense[::-1]