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Generate a list using given frequency list
Generating a list using a given frequency list is a common problem in programming. The task involves creating a list of elements based on the frequency distribution of those elements. This can be useful in many scenarios, such as generating a password with a specific character distribution or generating random sentences with specific word frequencies. In this article, we will explore how to generate a list using a given frequency list in Python.
Installation and Syntax
Python is a popular programming language for analyzing and modifying data, and it provides the Counter module from the collections package to make a list using a given frequency list. This module provides a useful technique for calculating the number of times a specific item appears in a list or other iterable.
Here is the syntax to import the Counter module −
from collections import Counter
One thing to bear in mind when creating a list using a specified frequency list is that, because the process is random, the created list could not exactly match the required frequency distribution. Yet, the frequency distribution that results will be closer to the intended one the more components that are created.
Algorithm
Create a Counter object from the frequency list.
Get the total number of elements in the frequency list.
Create an empty list to store the generated elements.
Loop through the Counter object and generate elements based on their frequency.
Shuffle the generated list to ensure randomness.
Example
from collections import Counter
import random
freq_list = [('a', 4), ('b', 2), ('c', 1), ('d', 3)]
freq_dict = dict(freq_list)
counter_obj = Counter(freq_dict)
total_elements = sum(counter_obj.values())
generated_list = []
for element, frequency in counter_obj.items():
count = int((frequency / total_elements) * 10)
for i in range(count):
generated_list.append(element)
random.shuffle(generated_list)
print(generated_list)
Output
['a', 'c', 'd', 'd', 'a', 'a', 'a', 'd', 'b', 'b']
Python needs to import the Counter module from the collections package as well as the random module in order to generate a list using a provided frequency list. The frequency of the elements to be created may thus be represented by a frequency list made up of four tuples. When building a dictionary from the frequency list, the Counter module is useful since you can then feed this dictionary to the Counter function to create a Counter object. The next step is to add up the Counter object's values to determine how many elements there are overall in the frequency list.
Generate the list after you have the Counter object by making an empty list to hold the produced elements and by computing the proportion of the total items and multiplying by the required length of the resulting list, which in this case is 10, the Counter object is cycled around to generate elements depending on their frequency. The created element is added to the list the appropriate number of times based on frequency once the count of the items to be generated has been determined. The list is shuffled before being printed to the terminal to ensure unpredictability.
Applications
Generating a list using a given frequency list can be useful in many scenarios. For example −
Generating a password with a specific character distribution
Generating random sentences with specific word frequencies
Generating a dataset with specific class distributions for machine learning models
Generating a list of products with specific popularity ratings for recommendation systems
Conclusion
Programming problems frequently involve creating a list with a frequency list that has been provided and in this post, we looked at utilizing the Counter module from the collections package to create a list in Python using a provided frequency list. There are alternative ways to create a list in Python using a specified frequency list other than using the Counter module such as invoking the random sampling function offered by the numpy module, which accepts the element weights as an input.
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