VertexFrame covariance_matrix

---

covariance_matrix(self, data_column_names, matrix_name=None)

Calculate covariance matrix for two or more columns.

Parameters:

data_column_names : list

The names of the column from which to compute the matrix. Names should refer to a single column of type vector, or two or more columns of numeric scalars.

matrix_name : unicode (default=None)

The name of the new matrix.

Returns:

: Frame

A matrix with the covariance values for the columns.

This function applies only to columns containing numerical data.

Examples

Consider Frame my_frame, which contains the data

>>> my_frame.inspect()
 [#]  idnum  x1   x2   x3   x4
===============================
[0]      0  1.0  4.0  0.0  -1.0
[1]      1  2.0  3.0  0.0  -1.0
[2]      2  3.0  2.0  1.0  -1.0
[3]      3  4.0  1.0  2.0  -1.0
[4]      4  5.0  0.0  2.0  -1.0

my_frame.covariance_matrix computes the covariance on each pair of columns in the user-provided list.

>>> cov_matrix = my_frame.covariance_matrix(my_frame.column_names)
[===Job Progress===]

The resulting table (specifying all columns) is:

>>> cov_matrix.inspect()
[#]  idnum  x1    x2    x3    x4
=================================
[0]    2.5   2.5  -2.5   1.5  0.0
[1]    2.5   2.5  -2.5   1.5  0.0
[2]   -2.5  -2.5   2.5  -1.5  0.0
[3]    1.5   1.5  -1.5   1.0  0.0
[4]    0.0   0.0   0.0   0.0  0.0