How do you solve Word Frequency on LeetCode?

Word Frequency (LeetCode #192) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(n log n) time complexity and O(n) space complexity. Key insight: Using a hash map allows for efficient counting of word frequencies.

What is the brute force solution for Word Frequency?

The brute force approach for Word Frequency is Brute Force, with O(n²) time complexity and O(1) space complexity. The brute-force approach involves reading the file and counting the occurrences of each word using nested loops. This is straightforward but inefficient, as it repeatedly checks for each word's frequency. The optimal Optimal Solution approach improves this to O(n log n).

What algorithm or data structure is used to solve Word Frequency?

Word Frequency uses the following concepts: Shell. The recommended patterns to study are: Hash Map, Array.

What are the interview tips for Word Frequency?

Always clarify the input format and constraints before starting. Think about edge cases, such as empty files or files with only one word. Practice writing concise and efficient code, especially with data structures.

What are common mistakes when solving Word Frequency?

Not accounting for multiple spaces between words. Forgetting to handle the input file correctly.

#192

Word Frequency

Medium

ShellHash MapArray

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

	Brute Force	Optimal Solution★
Time	O(n²)	O(n log n)
Space	O(1)	O(n)

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Intuition

Time O(n log n)Space O(n)

The optimal solution leverages a single pass through the file to count word frequencies using a hash map, followed by sorting the results. This significantly reduces the time complexity compared to the brute-force approach.

⚙️

Algorithm

5 steps

1Step 1: Read the contents of the file and split it into words.
2Step 2: Use a hash map to count the occurrences of each word in a single pass.
3Step 3: Convert the hash map to a list of tuples for sorting.
4Step 4: Sort the list based on frequency in descending order.
5Step 5: Print the sorted list.

solution.py7 lines

1from collections import Counter
2
3with open('words.txt') as f:
4    words = f.read().split()
5    counts = Counter(words)
6    for word, freq in counts.most_common():
7        print(word, freq)

ℹ

Complexity note: The time complexity is O(n log n) due to the sorting step, while the space complexity is O(n) for storing the word counts in a hash map.

1Using a hash map allows for efficient counting of word frequencies.
2Sorting the results is necessary for presenting the output in the required order.

Solutions and explanations are original Tejav content. Problem titles © LeetCode — use the LeetCode button above for the full problem statement.