Usually when doing machine learning problems, you need to prepare training data, usually the sample data and labels are stored in 2 lists, such as train_x = [x1,x2,...,xN] $[{\mathbf{x}}_1,{\mathbf{x}}_2,...,{\mathbf{x}}_N]$，train_y = [y1,y2,...,yN] $[y_1,y_2,...,y_N]$. Sometimes it is necessary to shuffle the data before processing (for example, batch gradient descent algorithm, the data needs to be shuffled). At this time, you need to shuffle the two lists in the same order, so how to achieve it in python? This can be achieved by setting the same random seed and then shuffle. code show as below:

import random

randnum = random.randint(0,100)
random.seed(randnum)
random.shuffle(train_x)
random.seed(randnum)
random.shuffle(train_y)