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