.corr()

Series.corr(other, method=’pearson’, min_periods=None)

Compute correlation with other Series, excluding missing values.

>>> histogram_intersection = lambda a, b: np.minimum(a, b).sum().round(decimals=1)
>>> s1 = pd.Series([.2, .0, .6, .2])
>>> s2 = pd.Series([.3, .6, .0, .1])
>>> s1.corr(s2, method=histogram_intersection)
0.3

DataFrame.corr(method=’pearson’, min_periods=1)

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

>>> 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