pandas.core.groupby.DataFrameGroupBy.corr¶
-
DataFrameGroupBy.
corr
¶ 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 .. 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: - y : DataFrame
See also
DataFrame.corrwith
,Series.corr
Examples
>>> histogram_intersection = lambda a, b: np.minimum(a, b ... ).sum().round(decimals=1) >>> 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