Classe « Series »

Méthode pandas.Series.corr

Signature de la méthode corr

def corr(self, other, method='pearson', min_periods=None) -> float 

Description

corr.__doc__

        Compute correlation with `other` Series, excluding missing values.

        Parameters
        ----------
        other : Series
            Series with which to compute the correlation.
        method : {'pearson', 'kendall', 'spearman'} or callable
            Method used to compute correlation:

            - pearson : Standard correlation coefficient
            - kendall : Kendall Tau correlation coefficient
            - spearman : Spearman rank correlation
            - callable: Callable with input two 1d ndarrays and returning a float.

            .. versionadded:: 0.24.0
                Note that the returned matrix from corr will have 1 along the
                diagonals and will be symmetric regardless of the callable's
                behavior.
        min_periods : int, optional
            Minimum number of observations needed to have a valid result.

        Returns
        -------
        float
            Correlation with other.

        See Also
        --------
        DataFrame.corr : Compute pairwise correlation between columns.
        DataFrame.corrwith : Compute pairwise correlation with another
            DataFrame or Series.

        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