Python - How To Find the Most Common Elements of a List in Python

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This article mentions several ways to find the most common elements of a list in Python. The following are the functions that we can use to find the most common list elements in Python.

  • Use the most_common() function of Counter.
  • Use the max() function of FreqDist().
  • Use the unique()function of NumPy.

Use the most_common() of Counter to Find the Most Common Elements of a List in Python

In Python 2.7+, use the Counter() command to find the most common list elements in Python. For this, you need to import the Counter class from the collections standard library.

A Counter is a collection where elements are stored as dictionary keys, and the key’s counts are stored as dictionary values. The example below illustrates this.

list_of_words=['Cars', 'Cats', 'Flowers', 'Cats','Cats','Cats'] from collections import Counter c = Counter(list_of_words) c.most_common(1) print ("",c.most_common(1)) 

Here, the top one element is determined by using the most_common() function as most_common(1).

Output:

[('Cats', 4)] 

Use the max() Function of FreqDist() to Find the Most Common Elements of a List in Python

You can also use the max() command of FreqDist() to find the most common list elements in Python. For this, you import the nltk library first. The example below demonstrates this.

import nltk list_of_words=['Cars', 'Cats', 'Flowers', 'Cats'] frequency_distribution = nltk.FreqDist(list_of_words)  print("The Frequency distribution is -",frequency_distribution) most_common_element = frequency_distribution.max() print ("The most common element is -",most_common_element) 

Here, the frequency distribution list is first built using the FreqDist() function, and then the most common element is determined by using the max() function.

Output:

The Frequency distribution is - <FreqDist with 3 samples and 4 outcomes> The most common element is - Cats 

Use the unique() Function of NumPy to Find the Most Common Elements of a List in Python

Lastly, you can use the NumPy library’s unique() function to find the most common elements of a list in Python. The following example below illustrates this.

import numpy list_of_words=['Cars', 'Cats', 'Flowers', 'Cats', 'Horses', '', 'Horses', 'Horses', 'Horses'] fdist=dict(zip(*numpy.unique(list_of_words, return_counts=True))) print("The elements with their counts are -", fdist) print("The most common word is -",list(fdist)[-1]) 

The output of this operation is a dictionary of key-value pairs, where the value is the count of a particular word. Use the unique() function to find the unique elements of an array. Next, the zip() command is used to map the similar index of multiple containers. In this example, we use it to get the frequency distribution. Since the output lists the key-value pairs in ascending order, the most common element is determined by the last element.

Output:

The elements with their counts are - {'': 1, 'Cars': 1, 'Cats': 2, 'Flowers': 1, 'Horses': 4} The most common word is - Horses 

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