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ENH: Allow pairwise calcuation when comparing the column with itself … #43569

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ENH: Allow pairwise calcuation when comparing the column with itself … #43569

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BUG: Allow pairwise calcuation when comparing the column with itself …
Sep 13, 2021
d6ac406
Merge branch 'master' into pairwise
jreback Oct 21, 2021
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1 change: 1 addition & 0 deletions doc/source/whatsnew/v1.4.0.rst
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Expand Up @@ -129,6 +129,7 @@ Other enhancements
- :meth:`DataFrame.__pos__`, :meth:`DataFrame.__neg__` now retain ``ExtensionDtype`` dtypes (:issue:`43883`)
- The error raised when an optional dependency can't be imported now includes the original exception, for easier investigation (:issue:`43882`)
- Added :meth:`.ExponentialMovingWindow.sum` (:issue:`13297`)
- :meth:`DataFrame.corr` now accept the argument ``calculate_diagonal`` to allow results returned from callable to be used as diagonal elements of the correlation matrix instead of setting them to ones (:issue:`25781`)

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

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9 changes: 8 additions & 1 deletion pandas/core/frame.py
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Expand Up @@ -9402,6 +9402,7 @@ def corr(
self,
method: str | Callable[[np.ndarray, np.ndarray], float] = "pearson",
min_periods: int = 1,
calculate_diagonal: bool = False,
) -> DataFrame:
"""
Compute pairwise correlation of columns, excluding NA/null values.
Expand All @@ -9422,6 +9423,12 @@ def corr(
Minimum number of observations required per pair of columns
to have a valid result. Currently only available for Pearson
and Spearman correlation.
calculate_diagonal : bool, optional
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this is descriptive, but is there precedent for this type of naming, e.g numpy?

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@peterpanmj peterpanmj Sep 30, 2021 •
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this is descriptive, but is there precedent for this type of naming, e.g numpy?

No. I came up with this myself. I'm not familiar with Numpy naming convention. Any suggestion ?

Whether to calculate pairwise correlation using supplied callable.
Ignored when method argument is not callable. If False, pairwise
correlation between a column and itself is default to 1.

.. versionadded:: 1.4.0

Returns
-------
Expand Down Expand Up @@ -9471,7 +9478,7 @@ def corr(
valid = mask[i] & mask[j]
if valid.sum() < min_periods:
c = np.nan
elif i == j:
elif i == j and not calculate_diagonal:
c = 1.0
elif not valid.all():
c = corrf(ac[valid], bc[valid])
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15 changes: 15 additions & 0 deletions pandas/tests/frame/methods/test_cov_corr.py
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Expand Up @@ -236,6 +236,21 @@ def test_corr_min_periods_greater_than_length(self, method):
)
tm.assert_frame_equal(result, expected)

@pytest.mark.filterwarnings("ignore: An input array is constant")
@td.skip_if_no_scipy
@pytest.mark.parametrize("array_creator", [np.ones, np.zeros, np.random.random])
def test_corr_diagonal_not_ones(self, array_creator):
from scipy.stats import pearsonr

frame_size = 4
df = DataFrame(array_creator((frame_size, frame_size)))
cor_mat = df.corr(
method=lambda x, y: pearsonr(x, y)[0], calculate_diagonal=True
)
result_diag = [cor_mat.loc[i, i] for i in range(frame_size)]
expected_diag = [pearsonr(df[i], df[i])[0] for i in range(frame_size)]
tm.assert_almost_equal(result_diag, expected_diag)


class TestDataFrameCorrWith:
def test_corrwith(self, datetime_frame):
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