Correlation Matrix from Covariance

Problem

Convert a covariance matrix C into a correlation matrix:

R[i][j] = C[i][j] / sqrt(C[i][i] * C[j][j])

Return None if any variance C[i][i] is 0.

Hint

The result is the covariance rescaled by the standard deviations.

case 1

in: [[[4,2],[2,4]]]

expected: [[1,0.5],[0.5,1]]

case 2

in: [[[1,2],[2,4]]]

expected: [[1,1],[1,1]]

case 3

in: [[[1,0],[0,4]]]

expected: [[1,0],[0,1]]

case 4

in: [[[1,0.5],[0.5,0]]]

expected: null

Starter codePython

def correlation_matrix(C):
    # Your code here
    pass

4 test cases · run your code against them in the editor