pandas.DataFrame.corr — pandas 0.24.0rc1 documentation (original) (raw)

DataFrame. corr(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 .. 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

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

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