Frame correlation

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correlation(self, data_column_names)

Calculate correlation for two columns of current frame.

Parameters:

data_column_names : list

The names of 2 columns from which to compute the correlation.

Returns:

: dict

Pearson correlation coefficient of the two columns.

This method applies only to columns containing numerical data.

Examples

Consider Frame my_frame, which contains the data

 >>> my_frame.inspect()

  idnum:int32   x1:float32   x2:float32   x3:float32   x4:float32
/-------------------------------------------------------------------/
            0          1.0          4.0          0.0         -1.0
            1          2.0          3.0          0.0         -1.0
            2          3.0          2.0          1.0         -1.0
            3          4.0          1.0          2.0         -1.0
            4          5.0          0.0          2.0         -1.0

my_frame.correlation computes the common correlation coefficient (Pearson’s) on the pair of columns provided. In this example, the idnum and most of the columns have trivial correlations: -1, 0, or +1. Column x3 provides a contrasting coefficient of 3 / sqrt(3) = 0.948683298051 .

>>> my_frame.correlation(["x1", "x2"])
   -1.0
>>> my_frame.correlation(["x1", "x4"])
    0.0
>>> my_frame.correlation(["x2", "x3"])
    -0.948683298051