Table of Contents
In this article we will learn how to shuffle two np arrays together. We will first learn a bit about numpy library and arrays and then we will proceed to learn how to shuffle two np arrays together.
The Numpy Module
Numpy is the library used for handling arrays in python. It has many in-built functions that help greatly while dealing with arrays. The code base of numpy library can be found on Github. It is an open source library.
Why Use Numpy for Arrays?
In python we use lists as arrays. But the processing of lists is slow and Numpy provides Arrays objects that are 50 times faster than lists. The reason for numpy arrays being faster is that they use continuous memory which optimize the memory allocation process.
The installation process is easy, you have to type in the following command to the terminal
pip install numpy
The output must be something like this
Collecting numpy Downloading numpy-1.23.3-cp310-cp310-win_amd64.whl (14.6 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 14.6/14.6 MB 1.7 MB/s eta 0:00:00 Installing collected packages: numpy Successfully installed numpy-1.23.3
How to shuffle two np arrays together
The first approach is rather simple and a naive approach but it can shuffle the arrays. We will randomize the array indexes by using the random shuffle method, and assign these random indexes to the array, to shuffle two np arrays together this can work. The code is written below
import numpy as np # shuffle two np arrays together x=np.array([1,2,4,4,3,6]) y=np.array([1,9,7,4,6,7]) r_indexes = np.arange(len(x)) np.random.shuffle(r_indexes) x = x[r_indexes] y = y[r_indexes] print(x) print(y)
The output of this code will be random, lets run the code three times and check if the output is different.
First run :
shuffle two np arrays together the x array after shuffling becomes : [6 2 4 4 1 3] the y array after shuffling becomes [7 9 4 7 1 6]
Second run :
shuffle two np arrays together the x array after shuffling becomes : [1 2 6 3 4 4] the y array after shuffling becomes [1 9 7 6 4 7]
Third run :
shuffle two np arrays together the x array after shuffling becomes : [3 1 2 4 4 6] the y array after shuffling becomes [6 1 9 7 4 7]
Hence the results show that the shuffling is accurate, every time the arrays shuffle and give different result.
Second method is to use permutations, and shuffle the indexes. The code is written below
import numpy as np from numpy.random import permutation X = np.array([4,2,3,7,8]) Y =np.array([1,3,2,4,5]) perm = permutation(len(X)) X = X[perm] Y = Y[perm] print ("shuffle two np arrays together, X becomes ",X) print("and Y becomes ", Y)
The output for 3 runs will be different
shuffle two np arrays together, X becomes [2 4 8 7 3] and Y becomes [3 1 5 4 2]
shuffle two np arrays together, X becomes [8 2 3 4 7] and Y becomes [5 3 2 1 4]
shuffle two np arrays together, X becomes [4 7 8 3 2] and Y becomes [1 4 5 2 3]
In this article we learned how we can shuffle two np arrays together using permutations or randomize function from
np module. We also learned a bit about the