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Python | List frequency of elements
  • Last Updated : 21 Jan, 2021
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Sometimes we have the utility in which we require to find the frequency of elements in the list and the solution to this problem has been discussed many times. But sometimes we come across the task in which we require to find the number of lists that particular elements occur. Let’s discuss certain shorthands in which this can be done.
 

Method #1 : Using Counter() + set() + list comprehension 
The combination of the above functions can be used to perform the task. The Counter function does the grouping, set function extracts the distinct elements as keys of dict and list comprehension check for its list occurrences.
 

Python3




# Python3 code to demonstrate
# list frequency of elements
# using Counter() + set() + list comprehension
from collections import Counter
 
# initializing list
test_list = [[3, 5, 4],
             [6, 2, 4],
             [1, 3, 6]]
 
# printing original list
print("The original list : " + str(test_list))
 
# using Counter() + set() + list comprehension
# list frequency of elements
res = dict(Counter(i for sub in test_list for i in set(sub)))
 
# printing result
print("The list frequency of elements is : " + str(res))
Output : 
The original list : [[3, 5, 4], [6, 2, 4], [1, 3, 6]]
The list frequency of elements is : {1: 1, 2: 1, 3: 2, 4: 2, 5: 1, 6: 2}

 

 
Method #2 : Using Counter() + itertools.chain.from_iterable() + map() + set() 
The above 4 functionalities can also be combined to achieve this particular task. The set function extracts the dictionary keys formed by the Counter, map function performs the task for all sublists and from_iterable function performs using iterators which is faster than list comprehension.
 

Python3




# Python3 code to demonstrate
# list frequency of elements
# using Counter() + itertools.chain.from_iterable() + map() + set()
from collections import Counter
from itertools import chain
 
# initializing list
test_list = [[3, 5, 4],
             [6, 2, 4],
             [1, 3, 6]]
 
# printing original list
print("The original list : " + str(test_list))
 
# using Counter() + itertools.chain.from_iterable() + map() + set()
# list frequency of elements
res = dict(Counter(chain.from_iterable(map(set, test_list))))
 
# printing result
print("The list frequency of elements is : " + str(res))
Output : 



The original list : [[3, 5, 4], [6, 2, 4], [1, 3, 6]]
The list frequency of elements is : {1: 1, 2: 1, 3: 2, 4: 2, 5: 1, 6: 2}

 

Method #3: Using python dictionary + get() method

Python dictionary provides a get method which returns the value corresponding to the key and if the key does not exist in the dictionary then it provides functionality to create the key and assign it a default value. We will use this functionality of a dictionary.

Python3




d = {}
 
test_list = [[3, 5, 4],
             [6, 2, 4],
             [1, 3, 6]]
 
for x in test_list:
  for i in x:
    d[i] = d.get(i,0) + 1
 
# Orignal list
print(f"The original list : {test_list}" )
 
# printing result
print(f"The list frequency of elements is : {d}" )

Output:

The original list : [[3, 5, 4], [6, 2, 4], [1, 3, 6]]
The list frequency of elements is : {3: 2, 5: 1, 4: 2, 6: 2, 2: 1, 1: 1}

Method #4: Using Pandas 

In this method we will use a python module named pandas(You can know more about pandas in this article) to find the frequency of the given data, here below is the code for it.

Python3




import pandas as pd
 
test_list = [3,5,4,3,3,4,5,2]
 
df1 = pd.Series(test_list).value_counts().sort_index().reset_index().reset_index(drop=True)
df1.columns = ['Element', 'Frequency']
 
# Orignal list
print(f"The original list : {test_list}" )
 
# printing result
print(f"The list frequency of elements is :\n {df1.to_string(index=False)}" )

Output:

The original list : [3, 5, 4, 3, 3, 4, 5, 2]
The list frequency of elements is :
Element  Frequency
  2          1
  3          3       
  4          2
  5          2

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