Robust Scaling

Problem

Scale values robustly: (x_i - median) / IQR, where IQR = Q3 - Q1. Q1 is the median of the lower half of the sorted values and Q3 is the median of the upper half; for an odd count, exclude the median element itself from both halves.

If the IQR is 0, return a list of zeros. Empty input returns [].

Hint

Median-center, then divide by the interquartile range.

Test cases

case 1

in: [[1,2,3,4,5,6,7,8]]

expected: [-0.875,-0.625,-0.375,-0.125,0.125,0.375,0.625,0.875]

case 2

in: [[1,2,3,4,5]]

expected: [-0.6666666666666666,-0.3333333333333333,0,0.3333333333333333,0.6666666666666666]

case 3

in: [[7,7,7]]

expected: [0,0,0]

case 4

in: [[1,2,3,4]]

expected: [-0.75,-0.25,0.25,0.75]

Starter codePython

def robust_scale(values):
    # Your code here
    pass

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