Choose element(s) from List with different probability in Python
Last Updated :
11 Oct, 2020
Have you ever wondered how to select random elements from a list with different probability in Python? In this article, we will discuss how to do the same. Let’s first consider the below example.
Python3
import random
sam_Lst = [10, 20, 3, 4, 100]
ran = random.choice(sam_Lst)
print(ran)
|
In the above example, the probability of getting any element from the list is equal. But we want such methods in which the probability of choosing one element from the list is different. This is known as the weighted random choice in Python. In order to find weighted random choices in Python, there exist two ways:
- Relative weights
- Cumulative weights
The function which will help us in this situation is random.choices(). This function allows making weighted random choices in python with replacement.
Syntax:
random.choices(population, weights=None, *, cum_weights=None, k=1)
Here, the ‘weight’ parameter plays an important role.
Case 1: Using Relative weights
The weight assigned to an element is known as relative weight.
Example 1:
Python3
import random
num_lst = [1, 22, 43, 19, 13, 29]
print(random.choices(num_lst, weights=(
14, 25, 30, 45, 55, 10), k=6))
|
Output:
[19, 19, 13, 22, 13, 13]
In the above example, we assign weights to every element of the list. The weight of the element ‘13′ is highest i.e 55, so the probability of its occurrence is maximum. As we can see in the output, element 13 occurs 3 times, 19 occurs 2 times, and so on. So, now the probability of choosing an element from the list is different.
Example 2:
Python3
import random
name_lst = ['October', 'November', 'December',
'January', 'March', 'June']
print(random.choices(name_lst, weights=(
40, 25, 30, 5, 15, 80), k=3))
|
Output:
['June', 'October', 'June']
In the above example, the weight of element ‘June’ is maximum so its probability of selection will be maximum. And here, k=3 which means we are choosing only the top 3 elements from the list.
Example 3:
Python3
import random
name_lst = ['Fit', 'Infected', 'Recovered', 'Danger']
for i in range(6):
print("Random choice", i+1)
randomele = random.choices(name_lst, weights=(
50, 80, 10, 5), k=1)
print(randomele[0])
|
Output:
Random choice 1
Recovered
Random choice 2
Danger
Random choice 3
Infected
Random choice 4
Infected
Random choice 5
Infected
Random choice 6
Fit
In the above example, we use FOR loop to choose an element from a list with a different probability.
Case 2: Using Cumulative weights
The cumulative weight of an element is determined by adding the weight of its previous element and its own weight.
Example 1:
Python3
import random
num_lst = [1, 22, 93, 19, 13, 25]
print(random.choices(num_lst, cum_weights=(
7, 13, 15, 20, 25, 20), k=6))
|
Output:
[1, 22, 93, 22, 19, 1]
In the above example, the cumulative weight of element ‘19′ is maximum, so the probability of its selection will also be maximum.
Example 2:
Python3
import random
name_lst = ['October', 'November', 'December',
'January', 'March', 'June']
print(random.choices(name_lst, cum_weights=(
40, 20, 3, 7, 15, 15), k=3))
|
Output:
['January', 'March', 'January']
In the above example, we choose k=3 so we get the top 3 elements that have the maximum probability of selection.
Example 3:
Python3
import random
name_lst = ['October', 'November', 'December',
'January', 'March', 'June']
for i in range(6):
print("Random choice", i+1)
randomele = random.choices(name_lst, cum_weights=(
7, 13, 15, 20, 25, 20), k=1)
print(randomele[0])
|
Output:
Random choice 1
November
Random choice 2
January
Random choice 3
October
Random choice 4
December
Random choice 5
November
Random choice 6
January
In the above example, we use FOR loop to choose an element from a list with a different probability.
Note: The value of k depends on the users, and since its relative weight so the total sum of weights can exceed 100.
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