Python Program to Count Frequency of Words in String

Use collections.Counter with split() to count word frequency like this: from collections import Counter; counts = Counter(your_string.split()).

Examples

Inputhello world hello

Output{'hello': 2, 'world': 1}

Inputapple banana apple orange banana apple

Output{'apple': 3, 'banana': 2, 'orange': 1}

Input

Output{}

How to Think About It

To count how many times each word appears, first split the string into words using spaces. Then, for each word, keep track of how many times it shows up by adding one each time you see it. This way, you get a list of words with their counts.

Algorithm

1

Get the input string.

2

Split the string into words using spaces.

3

Create an empty dictionary to store word counts.

4

For each word in the list, increase its count in the dictionary by one.

5

Return or print the dictionary with word frequencies.

Code

python

from collections import Counter

def count_word_frequency(text):
    words = text.split()
    frequency = Counter(words)
    return dict(frequency)

# Example usage
input_text = "hello world hello"
print(count_word_frequency(input_text))

Output

{'hello': 2, 'world': 1}

Dry Run

Let's trace the input 'hello world hello' through the code

1

Split the string

words = ['hello', 'world', 'hello']

2

Count words using Counter

frequency = Counter({'hello': 2, 'world': 1})

3

Convert Counter to dictionary

result = {'hello': 2, 'world': 1}

Word	Count
hello	2
world	1

Why This Works

Step 1: Splitting the string

Using split() breaks the string into a list of words separated by spaces.

Step 2: Counting words

Counter automatically counts how many times each word appears in the list.

Step 3: Returning the result

Converting the Counter to a dictionary makes it easy to read and use the word counts.

Alternative Approaches

Manual dictionary counting

python

def count_word_frequency_manual(text):
    words = text.split()
    frequency = {}
    for word in words:
        if word in frequency:
            frequency[word] += 1
        else:
            frequency[word] = 1
    return frequency

print(count_word_frequency_manual('hello world hello'))

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

Using defaultdict from collections

python

from collections import defaultdict

def count_word_frequency_defaultdict(text):
    words = text.split()
    frequency = defaultdict(int)
    for word in words:
        frequency[word] += 1
    return dict(frequency)

print(count_word_frequency_defaultdict('hello world hello'))

This approach avoids checking if a word exists in the dictionary by using defaultdict, making code cleaner.

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

Time Complexity

The program processes each word once, so the time grows linearly with the number of words, O(n).

Space Complexity

It stores counts for each unique word, so space depends on the number of unique words, O(k).

Which Approach is Fastest?

Using Counter is fastest and most readable; manual counting is slower and more code.

Approach	Time	Space	Best For
collections.Counter	O(n)	O(k)	Simple and fast counting
Manual dictionary	O(n)	O(k)	No imports, basic Python
defaultdict	O(n)	O(k)	Cleaner manual counting