Python - Odd Frequency Characters

In Python, fetching characters with odd frequencies from a given string can be a very common task in text processing and data analysis. In this article, we will learn various methods to fetch the odd frequency characters of a string in Python.

Using a Dictionary

Dictionaries are very convenient when there is a need to keep track of the frequencies of elements

Approach

To get the odd frequency elements, We will iterate through the entire string, and for each character in the string, we will increment the character count in the dictionary. At the end of the iteration, we will be left with a dictionary having the count of occurrences of each character, then we will display the characters having the odd frequency.

Explanation

• Use a for loop to iterate through the string.

• For each character update its count in the dictionary, with the key as the character.

• Use the items() method to get the key, and value pairs from the dictionary and if the value is an odd number then append the character to the result list.

Example

st = "TutorialsPoint"

Occurrences = {}
result = []
   
# Populating dictionary with a count of each character
for char in st:
   Occurrences[char] = Occurrences.get(char, 0) + 1
# fetching characters with odd frequency
for char, count in Occurrences.items():
    if count % 2 != 0:
        result.append(char)
print(result)

Output

['T', 'u', 'r', 'a', 'l', 's', 'P', 'n']

Using a Counter

Python's Counter class from the collections module provides an easy way to count the frequency of elements in an iterable, including characters in a string. We can use this approach to simplify fetching characters with odd frequencies.

Syntax

Counter()

Counter(collection)

• Collection: list, tuple, string, etc.

Explanation

• Pass the string to the Counter()

• The Counter() will return a dictionary object, which contains the frequency of each character in the list.

• Iterate through the dictionary and append the characters having an odd frequency to the result list.

Example

from collections import Counter

Occurrences = Counter("TutorialsPoint")
result = []
for char, count in Occurrences.items():
    if count % 2 != 0:
        result.append(char)
   
print(result)

Output

['T', 'u', 'r', 'a', 'l', 's', 'P', 'n']

Using list comprehensions and the count() method

List comprehension provides a way to create lists based on existing lists or other iterables. we can use list comprehension along with the count method to count the frequency of each character in the string and construct a list of characters with odd frequencies.

Syntax

count()

count(element)

• element :item we want to count in the iterable.

• count() returns an integer, which is the count of the element.

Explanation

• Iterate through the string using list comprehension

• Get the list of unique characters in the string using set() method.

• If the count of characters is an odd number then add it to the list.

Example

st = "TutorialsPoint"
uniqueChars = set(st)
result = [char for char in uniqueChars if st.count(char) % 2 != 0]
print(result)

Output

['T', 'l', 'P', 'a', 'n', 's', 'r', 'u']

Using For Loop

We can use a nested loop to find the frequency of each character. For each character iterate through the entire list and increment the count value and if the count is odd add it to the result list.

Explanation

• Iterate through each element in the list

• For each element, check the occurrences of that element by iterating through the list.

• If the count is odd, add the element to the result list.

Example 4

st = "TutorialsPoint"

# getting distinct characters from string
uniqueChars = set(st)
result = []
for i in uniqueChars:
    count = 0
    for j in st:
        if(i==j):
            count= count+1
    if(count%2==1):
        result.append(i)
print(result)

Output

['T', 's', 'P', 'r', 'n', 'a', 'u', 'l']

Conclusion

In this tutorial, we have discussed multiple approaches to retrieve odd frequency characters from a string. The last approach we implemented is not very efficient and can be only used for small sized data, whereas the other three approaches can be used for large sized inputs.