Differing results from choice and choices in python random?

Question

I would have suspected the accompanying code return similar outcomes: 

import random

random.seed(765)

x = random.choices(range(34), k=100)

random.seed(765)

y = [random.choice(range(34)) for _ in range(100)]

But, When I compare:

>>> x[:5]

[1, 8, 9, 31, 29]

>>> y[:5]

[2, 30, 15, 26, 17]

obviously, x isn't identical to y. 

I speculate that I a missing something self-evident, however accepted the succession set by the seed would have returned similar 100 qualities, paying little mind to decision versus decisions with k = 100.

Answer 1

Your speculation is correct. In the given code, both x and y are generated using the same random seed, which should result in the same sequence of random numbers being generated. However, there is a difference in the way random.choices() and the list comprehension with random.choice() work, leading to different outcomes.

The random.choices() function returns a list of randomly selected elements from a population with replacement. In your case, it selects 100 elements from the range 0 to 33 with replacement. Since replacement is allowed, the same element can appear multiple times in the output list. As a result, x will contain 100 randomly selected values from the given range.

On the other hand, the list comprehension with random.choice() generates a new random value for each iteration without replacement. In each iteration, it selects one element from the range 0 to 33 randomly and without replacement. Therefore, y will contain 100 different random values from the given range.

That's why x and y are not identical. If you want x and y to have the same sequence of random numbers, you should use random.choices() in both cases. Here's an updated version of your code:

import random

random.seed(765)

x = random.choices(range(34), k=100)

random.seed(765)

y = random.choices(range(34), k=100)

print(x[:5])

print(y[:5])

Now, both x and y will contain the same sequence of 100 randomly selected values, as expected.

Answer 2

Check the documentaton:

For a given seed, the choices() function with equal weighting typically produces a different sequence than repeated calls to choice(). The algorithm used by choices() uses floating point arithmetic for internal consistency and speed. The algorithm used by choice() defaults to integer arithmetic with repeated selections to avoid small biases from round-off error.

Interested to learn the concepts of Python in detail? Come and join the python course to gain more knowledge in Python

Watch this video tutorial for more information.

Answer 3

Certainly! In the provided code, there is a difference in the generated outcomes of x and y, even though they both use the same random seed. This difference arises due to the distinction between random.choices() and the list comprehension with random.choice().

When using random.choices(), a list is created by randomly selecting elements from a given population with replacement. In this case, the range from 0 to 33 is the population, and 100 elements are selected with replacement. As a result, x will contain a list of 100 randomly chosen values from the given range, where duplication of elements is allowed.

On the other hand, the list comprehension with random.choice() generates a new random value for each iteration without replacement. It selects one element randomly from the range 0 to 33 in each iteration, ensuring that each value appears only once in the resulting list. Therefore, y will contain 100 distinct random values from the range.

Hence, the use of random.choices() in both cases would have produced identical outcomes. By doing so, x and y would have contained the same sequence of 100 randomly selected values, regardless of replacement or non-replacement.

Here's an updated version of the code with random.choices() used for both x and y:

import random

random.seed(765)

x = random.choices(range(34), k=100)

random.seed(765)

y = random.choices(range(34), k=100)

print(x[:5])

print(y[:5])

With this modification, x and y will exhibit the same sequence of 100 randomly selected values, fulfilling the expectation.

Answer 4

Despite using the same random seed, there is a noticeable distinction between the generated outcomes of x and y in the given code. This difference can be attributed to the variance between random.choices() and the list comprehension with random.choice().

When utilizing random.choices(), a list is created by randomly selecting elements from a specified population with replacement. In this case, the population consists of numbers ranging from 0 to 33, and 100 elements are selected with the possibility of duplicates. Consequently, x will contain a list of 100 randomly chosen values from the provided range, with the potential for repeated elements.

Conversely, the list comprehension with random.choice() generates a new random value for each iteration without replacement. It selects one element randomly from the range of 0 to 33 during each iteration, ensuring that each value appears only once in the resulting list. Hence, y will consist of 100 distinct random values chosen from the given range.

Thus, even though both x and y employ the same random seed, they yield different outcomes. If the goal is to have x and y exhibit the same sequence of random numbers, utilizing random.choices() in both cases is recommended.

Here's an updated rendition of the code:

import random

random.seed(765)

x = random.choices(range(34), k=100)

random.seed(765)

y = random.choices(range(34), k=100)

print(x[:5])

print(y[:5])

With this modification, x and y will encompass the identical sequence of 100 randomly selected values, regardless of the inclusion or exclusion of replacement.