pandas.Series.corr

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

Compute correlation with other Series, excluding missing values.

Parameters:

other : Series 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_periods : int, 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