scipy.stats.mstats.count_tied_groups#

scipy.stats.mstats.count_tied_groups(x, use_missing=False)[source]#

Counts the number of tied values.

Parameters:

xsequence: Sequence of data on which to counts the ties
use_missingbool, optional: Whether to consider missing values as tied.

Returns:

count_tied_groupsdict: Returns a dictionary (nb of ties: nb of groups).

Examples

>>> 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)
{2: 1, 3: 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)
{2: 2, 3: 1}
>>> z[[1,-1]] = np.ma.masked
>>> mstats.count_tied_groups(z, use_missing=True)
{2: 2, 3: 1}