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REG: fix regression in df.corrwith on tied data when method is spearman #49032

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REG: fix regression in df.corrwith on tied data when method is spearman #49032

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d228d7b
Update frame.py
GYHHAHA Oct 10, 2022
e230225
Update test_cov_corr.py
GYHHAHA Oct 10, 2022
059effd
Update v1.5.1.rst
GYHHAHA Oct 10, 2022
6a898f0
add blank line
GYHHAHA Oct 10, 2022
8fd679d
use algos.rank_1d
GYHHAHA Oct 10, 2022
3528e40
add more tests
GYHHAHA Oct 11, 2022
12e9232
Update frame.py
GYHHAHA Oct 11, 2022
8578581
convert nullable to np.array for pearson
GYHHAHA Oct 11, 2022
93879df
Update test_cov_corr.py
GYHHAHA Oct 11, 2022
8ae9403
fix import and pre-commit
GYHHAHA Oct 12, 2022
2f3c952
put params into tests
GYHHAHA Oct 14, 2022
cef9e9a
remove pd namespace
GYHHAHA Oct 14, 2022
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1 change: 1 addition & 0 deletions doc/source/whatsnew/v1.5.1.rst
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Expand Up @@ -86,6 +86,7 @@ Fixed regressions
- Fixed regression in :meth:`DataFrame.apply` when passing non-zero ``axis`` via keyword argument (:issue:`48656`)
- Fixed regression in :meth:`Series.groupby` and :meth:`DataFrame.groupby` when the grouper is a nullable data type (e.g. :class:`Int64`) or a PyArrow-backed string array, contains null values, and ``dropna=False`` (:issue:`48794`)
- Fixed regression in :class:`ExcelWriter` where the ``book`` attribute could no longer be set; however setting this attribute is now deprecated and this ability will be removed in a future version of pandas (:issue:`48780`)
- Fixed regression in :meth:`DataFrame.corrwith` when computing correlation on tied data with ``method="spearman"`` (:issue:`48826`)

.. ---------------------------------------------------------------------------

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13 changes: 9 additions & 4 deletions pandas/core/frame.py
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Expand Up @@ -10598,18 +10598,23 @@ def corrwith(
cols = self.columns
ndf = self.values.transpose()
k = other.values
k_mask = ~np.isnan(k)
if k.dtype == "bool":
k = k.astype("float")
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Why are these casts needed? If needed, can it be converted to int instead?

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The bool type won't be accepted by rank_1d's signature.

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If we cast it to int, then nan in bool array will be -2147483648.

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rank should accept uint8, so k = k.view(uint8)

What happens with nullable dtypes?

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TypeError: No matching signature found

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rank_1d is compiled for uint8_t

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@GYHHAHA GYHHAHA Oct 11, 2022 •
edited
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Oh, sorry. My code was tested on 1.4.3.. I find the signature is changed in 1.5.0. as numeric_object_t instead of iu_64_floating_t. Now it works. Thanks. @phofl

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This worked on 1.4.4, so have to fix this too or revert as suggested in the issue

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Any reason we can't use pd.isna?

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change to pd.isna now

if method == "pearson":
for i, r in enumerate(ndf):
nonnull_mask = ~np.isnan(r) & ~np.isnan(k)
nonnull_mask = ~np.isnan(r) & k_mask
corrs[cols[i]] = np.corrcoef(r[nonnull_mask], k[nonnull_mask])[
0, 1
]
else:
for i, r in enumerate(ndf):
nonnull_mask = ~np.isnan(r) & ~np.isnan(k)
nonnull_mask = ~np.isnan(r) & k_mask
if r.dtype == "bool":
r = r.astype("float")
corrs[cols[i]] = np.corrcoef(
r[nonnull_mask].argsort().argsort(),
k[nonnull_mask].argsort().argsort(),
libalgos.rank_1d(r[nonnull_mask]),
libalgos.rank_1d(k[nonnull_mask]),
)[0, 1]
return Series(corrs)
else:
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9 changes: 9 additions & 0 deletions pandas/tests/frame/methods/test_cov_corr.py
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Expand Up @@ -399,6 +399,15 @@ def test_corrwith_spearman(self):
expected = Series(np.ones(len(result)))
tm.assert_series_equal(result, expected)

@td.skip_if_no_scipy
def test_corrwith_spearman_with_tied_data(self):
# GH#48826
df = DataFrame({"A": [2, np.nan, 8, 9], "B": [0, 1, 1, 0]})
s = Series([0, 1, 1, 0])
result = df.corrwith(s, method="spearman")
expected = Series([0.0, 1.0], index=["A", "B"])
tm.assert_series_equal(result, expected)

@td.skip_if_no_scipy
def test_corrwith_kendall(self):
# GH#21925
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