Python Program to Find Most Frequent Word in String

Use collections.Counter to count words and most_common(1) to find the most frequent word like this: most_frequent = Counter(text.split()).most_common(1)[0][0].

Examples

Inputapple banana apple orange banana apple

Outputapple

Inputhello world hello

Outputhello

Input

Output

How to Think About It

To find the most frequent word, first split the string into words. Then count how many times each word appears. Finally, find the word with the highest count and return it.

Algorithm

1

Get the input string.

2

Split the string into a list of words.

3

Count the frequency of each word.

4

Find the word with the highest frequency.

5

Return that word.

Code

python

from collections import Counter

def most_frequent_word(text):
    if not text:
        return ""
    words = text.split()
    count = Counter(words)
    return count.most_common(1)[0][0]

# Example usage
input_text = "apple banana apple orange banana apple"
print(most_frequent_word(input_text))

Output

apple

Dry Run

Let's trace the input 'apple banana apple orange banana apple' through the code

1

Split the string

words = ['apple', 'banana', 'apple', 'orange', 'banana', 'apple']

2

Count word frequencies

count = {'apple': 3, 'banana': 2, 'orange': 1}

3

Find most common word

most_common(1) returns [('apple', 3)]

4

Return the word

Return 'apple'

Word	Count
apple	3
banana	2
orange	1

Why This Works

Step 1: Splitting the string

We use split() to break the string into words so we can count each one separately.

Step 2: Counting words

The Counter creates a dictionary where keys are words and values are how many times they appear.

Step 3: Finding the most frequent word

The most_common(1) method returns the word with the highest count, which we then return.

Alternative Approaches

Using a dictionary manually

python

def most_frequent_word_manual(text):
    if not text:
        return ""
    words = text.split()
    freq = {}
    for word in words:
        freq[word] = freq.get(word, 0) + 1
    max_word = max(freq, key=freq.get)
    return max_word

print(most_frequent_word_manual("apple banana apple orange banana apple"))

This method uses basic dictionary operations without importing Counter, but is longer and less concise.

Using collections.defaultdict

python

from collections import defaultdict

def most_frequent_word_defaultdict(text):
    if not text:
        return ""
    words = text.split()
    freq = defaultdict(int)
    for word in words:
        freq[word] += 1
    max_word = max(freq, key=freq.get)
    return max_word

print(most_frequent_word_defaultdict("apple banana apple orange banana apple"))

This uses defaultdict for counting, which is a bit more efficient than manual dictionary checks.

Complexity: O(n) time, O(n) space

Time Complexity

Splitting the string and counting words both take O(n) time where n is the number of words.

Space Complexity

We store counts for each unique word, which can be up to O(n) in the worst case.

Which Approach is Fastest?

Using collections.Counter is fastest and most readable; manual dictionary methods are slightly slower and more verbose.

Approach	Time	Space	Best For
collections.Counter	O(n)	O(n)	Simplicity and speed
Manual dictionary	O(n)	O(n)	No imports, basic Python
defaultdict	O(n)	O(n)	Efficient counting without Counter