shuffle vs permute numpy

np.random.permutation has two differences from np.random.shuffle:

• if passed an array, it will return a shuffled copy of the array; np.random.shuffle shuffles the array inplace
• if passed an integer, it will return a shuffled range i.e. np.random.shuffle(np.arange(n))

If x is an integer, randomly permute np.arange(x). If x is an array, make a copy and shuffle the elements randomly.

The source code might help to understand this:

3280        def permutation(self, object x):...3307            if isinstance(x, (int, np.integer)):3308                arr = np.arange(x)3309            else:3310                arr = np.array(x)3311            self.shuffle(arr)3312            return arr

Adding on to what @ecatmur said, np.random.permutation is useful when you need to shuffle ordered pairs, especially for classification:

from np.random import permutationfrom sklearn.datasets import load_irisiris = load_iris()X = iris.datay = iris.target# Data is currently unshuffled; we should shuffle # each X[i] with its corresponding y[i]perm = permutation(len(X))X = X[perm]y = y[perm]

The permutation() method returns a re-arranged array (and leaves the original array un-changed),this method will keep the original array intact and will return a shuffled array, for example x = [1,4,2,8] is the original array and the permutation method will return the rearranged array (lets say [8,4,1,2]).Now,you have two arrays, original array and the rearranged array.

In the other hand,

The shuffle() method makes changes to the original array,for example x = [1,4,2,8] is the original array and the shuffle method will return the shuffled array(lets say shuffled array is [8,4,1,2]). Now , the original array itself got changed to the Shuffled array, and you are only left with the shuffled array.

Reference :-https://www.w3schools.com/python/numpy_random_permutation.asp