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. 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

Series.corr

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