dataFrame.columns.stat — corrPearson()

Description

The corrPearson() method of the stat object computes the Pearson correlation coefficient between two selected columns.

Signature

dataFrame.columns(...columnNames).stat.corrPearson()
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 Pearson correlation coefficient and related statistics.
corr (number)
The Pearson 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 Pearson correlation coefficient ranges from -1 to 1
  • A value close to 1 indicates a strong positive linear relationship.
  • A value close to -1 indicates a strong negative linear relationship.
  • A value close to 0 indicates little or no linear relationship.
  • The Pearson correlation coefficient is sensitive to outliers.
  • The p-value tests the null hypothesis that the population correlation coefficient is equal to zero.
  • The confidence score is calculated as 1 - p_value.

Example

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

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