maxframe.dataframe.DataFrame.corr#

DataFrame.corr(method='pearson', min_periods=1)#

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.

    Note

    kendall, spearman and callables not supported on multiple chunks yet.

  • 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:

Correlation matrix.

Return type:

DataFrame

See also

DataFrame.corrwith

Compute pairwise correlation with another DataFrame or Series.

Series.corr

Compute the correlation between two Series.

Examples

>>> import maxframe.dataframe as md
>>> df = md.DataFrame([(.2, .3), (.0, .6), (.6, .0), (.2, .1)],
...                   columns=['dogs', 'cats'])
>>> df.corr(method='pearson').execute()
          dogs      cats
dogs  1.000000 -0.851064
cats -0.851064  1.000000