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BUG: rank_2d raising with mixed dtypes #38932

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Merged
merged 8 commits into from
Jan 5, 2021
Merged

BUG: rank_2d raising with mixed dtypes #38932

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3858ca3
BUG: rank_2d mixed dtype
mzeitlin11 Jan 3, 2021
5c495f5
Add whatsnew
mzeitlin11 Jan 3, 2021
aebcde0
Merge remote-tracking branch 'upstream/master' into bug/rank_2d_mixed
mzeitlin11 Jan 4, 2021
4c1690c
Use argsort_indexer
mzeitlin11 Jan 4, 2021
743572b
Add back astype conversion
mzeitlin11 Jan 4, 2021
0b3d5e5
32-bit fixup
mzeitlin11 Jan 4, 2021
6edd2b3
Try intp
mzeitlin11 Jan 4, 2021
66504de
Update doc/source/whatsnew/v1.3.0.rst
jreback Jan 4, 2021
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2 changes: 2 additions & 0 deletions doc/source/whatsnew/v1.3.0.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -216,6 +216,8 @@ Numeric
- Bug in :meth:`DataFrame.select_dtypes` with ``include=np.number`` now retains numeric ``ExtensionDtype`` columns (:issue:`35340`)
- Bug in :meth:`DataFrame.mode` and :meth:`Series.mode` not keeping consistent integer :class:`Index` for empty input (:issue:`33321`)
- Bug in :meth:`DataFrame.rank` with ``np.inf`` and mixture of ``np.nan`` and ``np.inf`` (:issue:`32593`)
- Bug in :meth:`DataFrame.rank` with ``axis=0`` and columns holding incomparable types raising ``IndexError``
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if there is not issue (its fine don't create one), but add this PR number as the issue number.

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Thanks for committing that, yep no issue

-

Conversion
^^^^^^^^^^
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33 changes: 6 additions & 27 deletions pandas/_libs/algos.pyx
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Expand Up @@ -1112,7 +1112,6 @@ def rank_2d(
int tiebreak = 0
int64_t idx
bint check_mask, condition, keep_na
const int64_t[:] labels

tiebreak = tiebreakers[ties_method]

Expand Down Expand Up @@ -1158,34 +1157,14 @@ def rank_2d(

n, k = (<object>values).shape
ranks = np.empty((n, k), dtype='f8')
# For compatibility when calling rank_1d
labels = np.zeros(k, dtype=np.int64)

if rank_t is object:
try:
_as = values.argsort(1)
except TypeError:
values = in_arr
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This is the source of the bug - if axis=0, values is supposed to be transposed (as done earlier in the function) - setting equal to in_arr makes values the wrong shape since in_arr was not transposed

for i in range(len(values)):
ranks[i] = rank_1d(
in_arr[i],
labels=labels,
ties_method=ties_method,
ascending=ascending,
pct=pct
)
if axis == 0:
return ranks.T
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This whole try/except is not necessary because the except clause will always raise a TypeError anyway since if values.argsort(1) raises a TypeError, at least one column in values must not be sortable, so that same column will cause another TypeError to be raised when trying to fallback to rank_1d

else:
return ranks
if tiebreak == TIEBREAK_FIRST:
# need to use a stable sort here
_as = values.argsort(axis=1, kind='mergesort')
if not ascending:
tiebreak = TIEBREAK_FIRST_DESCENDING
else:
if tiebreak == TIEBREAK_FIRST:
# need to use a stable sort here
_as = values.argsort(axis=1, kind='mergesort')
if not ascending:
tiebreak = TIEBREAK_FIRST_DESCENDING
else:
_as = values.argsort(1)
_as = values.argsort(1)

if not ascending:
_as = _as[:, ::-1]
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12 changes: 12 additions & 0 deletions pandas/tests/frame/methods/test_rank.py
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Expand Up @@ -444,3 +444,15 @@ def test_rank_both_inf(self):
expected = DataFrame({"a": [1.0, 2.0, 3.0]})
result = df.rank()
tm.assert_frame_equal(result, expected)

@pytest.mark.parametrize(
"data,expected",
[
({"a": [1, 2, "a"], "b": [4, 5, 6]}, DataFrame({"b": [1.0, 2.0, 3.0]})),
({"a": [1, 2, "a"]}, DataFrame(index=range(3))),
],
)
def test_rank_mixed_axis_zero(self, data, expected):
df = DataFrame(data)
result = df.rank()
tm.assert_frame_equal(result, expected)