Pandas Series: corr() function

Compute correlation

The corr() function is used to compute correlation with other Series, excluding missing values.


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


Name Description Type/Default Value Required / Optional
other Series with which to compute the correlation. Series Required
  • 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
{‘pearson’, ‘kendall’, ‘spearman’} or callable Required
min_periods Minimum number of observations needed to have a valid result. int Optional

Returns: float
Correlation with other.


Python-Pandas Code:

import numpy as np
import pandas as pd
def histogram_intersection(p, q):
    v = np.minimum(p, q).sum().round(decimals=1)
    return v
s1 = pd.Series([.1, .0, .5, .1])
s2 = pd.Series([.2, .3, .0, .2])
s1.corr(s2, method=histogram_intersection)



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