pandas.DataFrame.corr¶

DataFrame.corr(method='pearson', min_periods=1)[source]¶

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

Parameters

method{‘pearson’, ‘kendall’, ‘spearman’} or callable

Method of correlation:

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.

min_periodsint, 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: Compute pairwise correlation with another DataFrame or Series.
Series.corr: Compute the correlation between two Series.

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

pandas.DataFrame.copy

pandas.DataFrame.corrwith