mars.dataframe.Series.corr#

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

Compute correlation with other Series, excluding missing values.

Parameters

  • other (Series) – Series with which to compute the correlation.

  • method ({'pearson', 'kendall', 'spearman'} or callable) –

    Method used to compute 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

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

  • min_periods (int, optional) – Minimum number of observations needed to have a valid result.

Returns

Correlation with other.

Return type

float

See also

DataFrame.corr

Compute pairwise correlation between columns.

DataFrame.corrwith

Compute pairwise correlation with another DataFrame or Series.

Examples

>>> import mars.dataframe as md
>>> s1 = md.Series([.2, .0, .6, .2])
>>> s2 = md.Series([.3, .6, .0, .1])
>>> s1.corr(s2, method='pearson').execute()
-0.8510644963469898