>>> import numpy as np
>>> y = np.array([1, 2, 2, 2, 2, 0, 2, 3, 3, 3, 0, 0, 2, 2, 0])
>>> np.count_nonzero(y == 1)
1
>>> np.count_nonzero(y == 2)
7
>>> np.count_nonzero(y == 3)
3
a = numpy.array([0, 3, 0, 1, 0, 1, 2, 1, 0, 0, 0, 0, 1, 3, 4])
unique, counts = numpy.unique(a, return_counts=True)
dict(zip(unique, counts))
# {0: 7, 1: 4, 2: 1, 3: 2, 4: 1}
unique, counts = numpy.unique(a, return_counts=True)# credit to Stack Overflow user in source link
# a is a numpy array
# Note: the following syntax allows you to count the number of elements x
# of the array such that 25 < x < 100
((a > 25) & (a < 100)).sum()