Pandas Series: corr() function

Last update on September 15 2022 12:58:05 (UTC/GMT +8 hours)

Compute correlation

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

Syntax:

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

Parameters:

Name	Description	Type/Default Value	Required / Optional
other	Series with which to compute the correlation.	Series	Required
method	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.

Example:

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)

Output:

0.2

Previous: Trim values at input in Pandas
Next: Count null observations in Pandas series