pandas.Series.corr — pandas 0.24.0rc1 documentation (original) (raw)

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

Compute correlation with other Series, excluding missing values.

Parameters:	other : Series 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 ndarray and returning a float .. versionadded:: 0.24.0 min_periods : int, optional Minimum number of observations needed to have a valid result
Returns:	correlation : float

Parameters:

other : Series 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 ndarray and returning a float .. versionadded:: 0.24.0 min_periods : int, optional Minimum number of observations needed to have a valid result

Returns:

correlation : float

Examples

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