pandas.Series.corr

Series.corr(self, other, method='pearson', min_periods=None)[source]

Compute correlation with other Series, excluding missing values.

Parameters
otherSeries

Series with which to compute the correlation.

method{‘pearson’, ‘kendall’, ‘spearman’} or callable
  • pearson : standard correlation coefficient

  • kendall : Kendall Tau correlation coefficient

  • spearman : Spearman rank correlation

  • 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_periodsint, optional

Minimum number of observations needed to have a valid result.

Returns
float

Correlation with other.

Examples

>>> def histogram_intersection(a, b):
...     v = np.minimum(a, b).sum().round(decimals=1)
...     return v
>>> s1 = pd.Series([.2, .0, .6, .2])
>>> s2 = pd.Series([.3, .6, .0, .1])
>>> s1.corr(s2, method=histogram_intersection)
0.3
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