Count Word Frequencies

Practice Exercise Beginner Easy Hash Map Hashing

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Problem

Implement word_frequencies(words). Return a dictionary mapping every token to its occurrence count.

Starter code

def word_frequencies(words):
    pass

Test cases

sample

{
  "args": [
    [
      "red",
      "blue",
      "red"
    ]
  ]
}

Expected: {"red":2,"blue":1}

Wizard outline

Step 1: Advance one frequency count
Initialize a missing word at one and increment an existing word. Every frequency map is built from the same local dictionary transition.
Step 2: Fold the transition over all words
Return the complete token-to-count mapping. Starting from an empty dictionary and applying the verified transition once per word preserves every occurrence.

Footguns and prerequisites

A dictionary comprehension records presence but loses repeated occurrences.
dictionaries and sets

Reviewed references

Python String Methods

Prepared Interview Problems

Group Words by Anagram Signature(opens in a new tab)
Counting tokens into a hash map rehearses the same frequency-signature construction used to place anagrams into canonical groups.

Recommended approach and implementation

Increment a dictionary entry for each token.

Why it works: Each loop adds one for exactly the current occurrence, so final values equal occurrence counts.

def _increment(counts, word):
    counts[word] = counts.get(word, 0) + 1
    return counts

def word_frequencies(words):
    counts = {}
    for word in words:
        _increment(counts, word)
    return counts

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