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Add option for alternative correlation types to DataFrame.corrwith() #21941

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Add option for alternative correlation types to DataFrame.corrwith() #21941

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20 changes: 9 additions & 11 deletions pandas/core/frame.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6891,7 +6891,7 @@ def cov(self, min_periods=None):

return self._constructor(baseCov, index=idx, columns=cols)

def corrwith(self, other, axis=0, drop=False):
def corrwith(self, other, axis=0, method='pearson', drop=False):
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Hmm...it would be safest to add it to the end of the signature, as this modification as it stands is not backwards compatible. Alternatively, you could issue a DeprecationWarning if a boolean is passed to method and re-assign it to drop.

"""
Compute pairwise correlation between rows or columns of two DataFrame
objects.
Expand All @@ -6901,6 +6901,10 @@ def corrwith(self, other, axis=0, drop=False):
other : DataFrame, Series
axis : {0 or 'index', 1 or 'columns'}, default 0
0 or 'index' to compute column-wise, 1 or 'columns' for row-wise
method : {'pearson', 'kendall', 'spearman'}
* pearson : standard correlation coefficient
* kendall : Kendall Tau correlation coefficient
* spearman : Spearman rank correlation
drop : boolean, default False
Drop missing indices from result, default returns union of all

Expand All @@ -6912,10 +6916,9 @@ def corrwith(self, other, axis=0, drop=False):
this = self._get_numeric_data()

if isinstance(other, Series):
return this.apply(other.corr, axis=axis)
return this.apply(other.corr, axis=axis, method=method)

other = other._get_numeric_data()

left, right = this.align(other, join='inner', copy=False)

# mask missing values
Expand All @@ -6926,14 +6929,9 @@ def corrwith(self, other, axis=0, drop=False):
left = left.T
right = right.T

# demeaned data
ldem = left - left.mean()
rdem = right - right.mean()

num = (ldem * rdem).sum()
dom = (left.count() - 1) * left.std() * right.std()

correl = num / dom
correl = Series(index=left.columns)
for col in left.columns:
correl[col] = nanops.nancorr(left[col], right[col], method=method)

if not drop:
raxis = 1 if axis == 0 else 0
Expand Down