Calculate the duplicate in multidimensional numpy array

Question

I am using python-3.x and I would like to calculate the number of duplicates in numpy array.... for example:

import numpy as np
my_array = np.array([[2, 3, 5],
                     [2, 3, 5], # duplicate of row 0 (this will be count as 1)
                     [2, 3, 5], # duplicate of row 0 (this will be count as 2)
                     [1, 0, 9], 
                     [3, 6, 6], 
                     [3, 6, 6], # duplicate of row 0 (this will be count as 3)
                     [1, 0, 9]])

What I would like to get from the outptu is the number of duplicates in this array:

the number of the duplicate is 3

most of the methods are returning the values such as collections.Counter or return_counts and they not returning what I want if I am using them right.

Any advice would be much appreciated

Anh Ngọc · Accepted Answer · 2019-01-23 00:36:23Z

1

You can get the duplicate count of array by take length of array - length of unique members of array:

the_number_of the duplicate = len(my_array) - len(np.unique(my_array, axis=0))

And the result of your example is 4 ([1,0,9] is duplicate also).

answered Jan 23, 2019 at 0:36

Anh Ngọc

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najeem · Accepted Answer · 2019-01-23 04:52:44Z

0

Here's a slight variation from @Anh Ngoc's answer. (for older versions of numpy where axis is not supported by np.unique)

number_of_duplicates = len(my_array) - len(set(map(tuple, my_array)))

answered Jan 23, 2019 at 4:52

najeem

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