`scipy.stats._mstats_basic:count_tied_groups`

Signature

def count_tied_groups(x, use_missing = False)

Counts the number of tied values.

count_tied_groups : dict: Returns a dictionary (nb of ties: nb of groups).

from scipy.stats import mstats
import numpy as np
z = [0, 0, 0, 2, 2, 2, 3, 3, 4, 5, 6]

✓

mstats.count_tied_groups(z)

✗

{np.int64(2): 1, np.int64(3): np.int64(2)}

In the above example, the ties were 0 (3x), 2 (3x) and 3 (2x).

z = np.ma.array([0, 0, 1, 2, 2, 2, 3, 3, 4, 5, 6])

✓

mstats.count_tied_groups(z)

✗

{np.int64(2): np.int64(2), np.int64(3): 1}

z[[1,-1]] = np.ma.masked

✓

mstats.count_tied_groups(z, use_missing=True)

✗

{np.int64(2): 2, np.int64(3): 1}