Shuffle two list at once with same order

Question

I\'m using the nltk library\'s movie_reviews corpus which contains a large number of documents. My task is get predictive performance of these reviews

Answer 1

Easy and fast way to do this is to use random.seed() with random.shuffle() . It lets you generate same random order many times you want. It will look like this:

a = [1, 2, 3, 4, 5]
b = [6, 7, 8, 9, 10]
seed = random.random()
random.seed(seed)
a.shuffle()
random.seed(seed)
b.shuffle()
print(a)
print(b)

>>[3, 1, 4, 2, 5]
>>[8, 6, 9, 7, 10]

This also works when you can't work with both lists at the same time, because of memory problems.

Answer 2

You can use the second argument of the shuffle function to fix the order of shuffling.

Specifically, you can pass the second argument of shuffle function a zero argument function which returns a value in [0, 1). The return value of this function fixes the order of shuffling. (By default i.e. if you do not pass any function as the second argument, it uses the function random.random(). You can see it at line 277 here.)

This example illustrates what I described:

import random

a = ['a', 'b', 'c', 'd', 'e']
b = [1, 2, 3, 4, 5]

r = random.random()            # randomly generating a real in [0,1)
random.shuffle(a, lambda : r)  # lambda : r is an unary function which returns r
random.shuffle(b, lambda : r)  # using the same function as used in prev line so that shuffling order is same

print a
print b

Output:

['e', 'c', 'd', 'a', 'b']
[5, 3, 4, 1, 2]

Answer 3

Shuffle an arbitray number of lists simultaneously.

from random import shuffle

def shuffle_list(*ls):
  l =list(zip(*ls))

  shuffle(l)
  return zip(*l)

a = [0,1,2,3,4]
b = [5,6,7,8,9]

a1,b1 = shuffle_list(a,b)
print(a1,b1)

a = [0,1,2,3,4]
b = [5,6,7,8,9]
c = [10,11,12,13,14]
a1,b1,c1 = shuffle_list(a,b,c)
print(a1,b1,c1)

Output:

$ (0, 2, 4, 3, 1) (5, 7, 9, 8, 6)
$ (4, 3, 0, 2, 1) (9, 8, 5, 7, 6) (14, 13, 10, 12, 11)

Note:
objects returned by shuffle_list() are tuples.

P.S. shuffle_list() can also be applied to numpy.array()

a = np.array([1,2,3])
b = np.array([4,5,6])

a1,b1 = shuffle_list(a,b)
print(a1,b1)

Output:

$ (3, 1, 2) (6, 4, 5)

Answer 4

You can do it as:

import random

a = ['a', 'b', 'c']
b = [1, 2, 3]

c = list(zip(a, b))

random.shuffle(c)

a, b = zip(*c)

print a
print b

[OUTPUT]
['a', 'c', 'b']
[1, 3, 2]

Of course, this was an example with simpler lists, but the adaptation will be the same for your case.

Hope it helps. Good Luck.

Answer 5

from sklearn.utils import shuffle

a = ['a', 'b', 'c','d','e']
b = [1, 2, 3, 4, 5]

a_shuffled, b_shuffled = shuffle(np.array(a), np.array(b))
print(a_shuffled, b_shuffled)

#random output
#['e' 'c' 'b' 'd' 'a'] [5 3 2 4 1]

Answer 6

I get a easy way to do this

import numpy as np
a = np.array([0,1,2,3,4])
b = np.array([5,6,7,8,9])

indices = np.arange(a.shape[0])
np.random.shuffle(indices)

a = a[indices]
b = b[indices]
# a, array([3, 4, 1, 2, 0])
# b, array([8, 9, 6, 7, 5])