Classe « DataFrame »

Méthode pandas.DataFrame.corr

Signature de la méthode corr

def corr(self, method='pearson', min_periods=1) -> 'DataFrame' 

Description

corr.__doc__

        Compute pairwise correlation of columns, excluding NA/null values.

        Parameters
        ----------
        method : {'pearson', 'kendall', 'spearman'} or callable
            Method of 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. 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 required per pair of columns
            to have a valid result. Currently only available for Pearson
            and Spearman correlation.

        Returns
        -------
        DataFrame
            Correlation matrix.

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

        Examples
        --------
        >>> def histogram_intersection(a, b):
        ...     v = np.minimum(a, b).sum().round(decimals=1)
        ...     return v
        >>> df = pd.DataFrame([(.2, .3), (.0, .6), (.6, .0), (.2, .1)],
        ...                   columns=['dogs', 'cats'])
        >>> df.corr(method=histogram_intersection)
              dogs  cats
        dogs   1.0   0.3
        cats   0.3   1.0