pandas.DataFrame.corr¶
-
DataFrame.
corr
(self, method='pearson', min_periods=1)[source]¶ Compute pairwise correlation of columns, excluding NA/null values.
Parameters: - 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 required per pair of columns to have a valid result. Currently only available for Pearson and Spearman correlation.
Returns: - DataFrame
Correlation matrix.
See also
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