how to get the value of multiple maximas in an array in python

Question

I have an array

a =[0,  0, 15, 17, 16, 17, 16, 12, 18, 18]

I am trying to find the element value that has max count. and if there is a tie, I would like all of the elements that have the same max count.

as you can see there are two 0, two 16, two 17, two 18 one 15 and one 12 so i want something that would return [0, 16, 17, 18] (order not important but I do not want the 15 or the 12)

I was doing np.argmax(np.bincount(a)) but argmax only returns one element (per its documentation) so I only get the 1st one which is 0

I tried np.argpartition(values, -4)[-4:] that works, but in practice I would not know that there are 4 elements that have the same count number! (maybe I am close here!!! the light bulb just went on !!!)

Answer 1

You can use np.unique to get the counts and an array of the unique elements then pull the elements whose count is equal to the max:

import numpy as np

a = np.array([0, 0, 15, 17, 16, 17, 16, 12, 18, 18])

un,  cnt = np.unique(a, return_counts=True)

print(un[cnt == cnt.max()])
[ 0 16 17 18]

un are the unique elements, cnt is the frequency/count of each:

In [11]: a = np.array([0, 0, 15, 17, 16, 17, 16, 12, 18, 18])

In [12]: un,  cnt = np.unique(a, return_counts=True)

In [13]: un, cnt
Out[13]: (array([ 0, 12, 15, 16, 17, 18]), array([2, 1, 1, 2, 2, 2]))

cnt == cnt.max() will give us the mask to pull the elements that are equal to the max:

In [14]: cnt == cnt.max()
Out[14]: array([ True, False, False,  True,  True,  True], dtype=bool)