Python: Calculate Redundancy Rate of a List

Question

I am trying to gauge the redundancy rate of a list.

Let's assume:

L = [a, a, a, a] => redundancy rate = 1

L = [a, b, c, d] => redundancy rate = 0

L = [a, a, b, b] => redundancy rate = 0.5

I couldn't end up with a meaningful way to do so.

Answer 1

Although the output matches the values in the problem description, I'm not quite sure if this is a valid measure. Maybe min is better than mean.

import pandas as pd
l1 = ['a', 'a', 'a', 'a']
l2= ['a', 'b', 'c', 'd']
l3 = ['a', 'a', 'b', 'b']

def f(l):
    s = pd.Series(l)
    ratio = s.value_counts() / len(l)
    redundantContent = s[s.duplicated(keep='first')]
    if not redundantContent.empty:
        return redundantContent.map(ratio).mean()
    else:
        return 0

print("redundancy rate of l1: {}".format(f(l1)))
print("redundancy rate of l2: {}".format(f(l2)))
print("redundancy rate of l3: {}".format(f(l3)))

Output

redundancy rate of l1: 1.0
redundancy rate of l2: 0
redundancy rate of l3: 0.5