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DOC: clarify corr behaviour when using a callable #25732

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Mar 18, 2019
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DOC: clarify corr behaviour when using a callable #25732

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5 changes: 3 additions & 2 deletions pandas/core/frame.py
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Expand Up @@ -7021,8 +7021,9 @@ def corr(self, method='pearson', min_periods=1):
* kendall : Kendall Tau correlation coefficient
* spearman : Spearman rank correlation
* callable: callable with input two 1d ndarrays
and returning a float

and returning a float. Note that the returned matrix from corr
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I am not sure this is needed to said. This is by-definition that same-same are correlated to 1.0

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if you want instead to add a link to a correlation matrix that would be ok

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I wanted to use the method argument of corr to compute p-values for the significance of the correlation. Then, the resulting matrix is not a correlation matrix anymore. Currently, pandas assumes that the callable supplied to method computes actual correlations, but this assumption is not explicitly mentioned. At least for me, it would have been helpful to know this behaviour.

will have 1 along the diagonals and will be symmetric
regardless of the callable's behavior
.. versionadded:: 0.24.0

min_periods : int, optional
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6 changes: 4 additions & 2 deletions pandas/core/series.py
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Expand Up @@ -2128,8 +2128,10 @@ def corr(self, other, method='pearson', min_periods=None):
* pearson : standard correlation coefficient
* kendall : Kendall Tau correlation coefficient
* spearman : Spearman rank correlation
* callable: callable with input two 1d ndarray
and returning a float
* callable: callable with input two 1d ndarrays
and returning a float. Note that the returned matrix from corr
will have 1 along the diagonals and will be symmetric
regardless of the callable's behavior
.. versionadded:: 0.24.0

min_periods : int, optional
Expand Down