`dataFrame.columns.stat — corrSpearman()`

Description

The corrSpearman() method of the stat object computes Spearman's rank correlation coefficient between two selected columns.

Signature

dataFrame.columns(...columnNames).stat.corrSpearman()

Scope: columns
Family: stat
Returns: object

Argument

...columnNames ( string[] ): The name of the columns from which to compute the correlation.

Returns

stat ( object[] )

A statistic object containing the Spearman rank correlation coefficient and related statistics.

corr (number): The Spearman rank correlation coefficient.
p_value (number): The p-value associated with the correlation.
confidence (number): A confidence score computed from the correlation p-value as 1 - p_value.

Notes

The method requires exactly two selected columns.
The Spearman correlation coefficient ranges from -1 to 1
A value close to 1 indicates a strong positive monotonic relationship.
A value close to -1 indicates a strong negative monotonic relationship.
A value close to 0 indicates little or no monotonic relationship.
The Spearman correlation coefficient is less sensitive to outliers than Pearson correlation.
The p-value tests the null hypothesis that the population rank correlation coefficient is equal to zero.
The confidence score is calculated as 1 - p_value.

Example

// evaluate a Spearman rank correlation for 2 columns of the dataFrame
var stat = dataFrame.columns('groupA', 'groupB').stat.corrSpearman();

// log the stat details
notebook.log(stat);