8000 CI: Update version of 'black' by MarcoGorelli · Pull Request #36493 · pandas-dev/pandas · GitHub
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CI: Update version of 'black' #36493

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Merged
merged 12 commits into from
Sep 22, 2020
Merged

CI: Update version of 'black' #36493

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dbf17ff
update black verison
MarcoGorelli Sep 20, 2020
4a32460
upgrade version of 'black'
MarcoGorelli Sep 20, 2020
30f2a59
rebase error
MarcoGorelli Sep 20, 2020
6259ded
rebase error continued
MarcoGorelli Sep 20, 2020
ebbef30
:art:
MarcoGorelli Sep 20, 2020
4c67eb7
pandas/tests/arrays/sparse/test_array.py
MarcoGorelli Sep 20, 2020
10eefa5
trailing commas
MarcoGorelli Sep 20, 2020
518f28b
trailing commas
MarcoGorelli Sep 20, 2020
c424404
generate_pip_deps_from_conda
MarcoGorelli Sep 20, 2020
b73d66a
remove trailing commas
MarcoGorelli Sep 20, 2020
7c019fd
Merge remote-tracking branch 'upstream/master' into update-black
MarcoGorelli Sep 21, 2020
5fd78c0
fix typing, use slice
MarcoGorelli Sep 21, 2020
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pandas/tests/arrays/sparse/test_array.py
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@MarcoGorelli
MarcoGorelli committed Sep 20, 2020
commit 4c67eb77670176fbe79754e23f701d60165dd041
15 changes: 12 additions & 3 deletions pandas/tests/arrays/sparse/test_array.py
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Original file line number Diff line number Diff line change
Expand Up @@ -193,7 +193,10 @@ def test_constructor_inferred_fill_value(self, data, fill_value):
assert result == fill_value

@pytest.mark.parametrize("format", ["coo", "csc", "csr"])
@pytest.mark.parametrize("size", [0, 10])
@pytest.mark.parametrize(
"size",
[0, 10],
)
@td.skip_if_no_scipy
def test_from_spmatrix(self, size, format):
import scipy.sparse
Expand Down Expand Up @@ -694,15 +697,21 @@ def test_getslice_tuple(self):
res = sparse[
4:,
] # noqa: E231
exp = SparseArray(np.array([0, 5, np.nan, np.nan, 0]))
exp = SparseArray(
dense[
4:,
]
) # noqa: E231
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Can the trailing comma be removed here? The explicit ignoring of Missing whitespace after ',', ';', or ':' (E231) suggests this is here on purpose

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Since dense is a 1D array, it should be the same to remove it I think

tm.assert_sp_array_equal(res, exp)

sparse = SparseArray(dense, fill_value=0)
res = sparse[
4:,
] # noqa: E231
exp = SparseArray(
np.array([0, 5, np.nan, np.nan, 0]),
dense[
4:,
],
fill_value=0,
) # noqa: E231
tm.assert_sp_array_equal(res, exp)
Expand Down
0