SyntaxShelf

Group anagrams

2 snippets in Interview Prep

DSAInterview Prep

Anagram Detection

DSA · Arrays & Strings
Syntax
Two strings are anagrams if they have identical character frequencies.
Approach 1: Sort both and compare.
Approach 2: Build frequency map and compare.
Example
// JavaScript
function isAnagram(s, t) {
  if (s.length !== t.length) return false;
  const freq = {};
  for (const ch of s) freq[ch] = (freq[ch] || 0) + 1;
  for (const ch of t) {
    if (!freq[ch]) return false;
    freq[ch]--;
  }
  return true;
}

# Python
def is_anagram(s, t):
    if len(s) != len(t):
        return False
    freq = {}
    for ch in s:
        freq[ch] = freq.get(ch, 0) + 1
    for ch in t:
        if freq.get(ch, 0) == 0:
            return False
        freq[ch] -= 1
    return True
Output
is_anagram('listen', 'silent') → True

Note Frequency map: O(n) time, O(1) space (bounded by alphabet size). Sorting approach: O(n log n). Always ask: are inputs lowercase only? Unicode? This affects space analysis. Follow-up: find all anagram groups in a list of words.

Group Anagrams

DSA · Hash Maps & Sets
Syntax
Use sorted string (or character frequency tuple) as hash map key.
All anagrams produce the same key.
Example
// JavaScript
function groupAnagrams(words) {
  const groups = new Map();
  for (const word of words) {
    const key = word.split('').sort().join('');
    if (!groups.has(key)) groups.set(key, []);
    groups.get(key).push(word);
  }
  return Array.from(groups.values());
}

# Python
def group_anagrams(words):
    groups = {}
    for word in words:
        key = ''.join(sorted(word))
        groups.setdefault(key, []).append(word)
    return list(groups.values())
Output
group_anagrams(['eat','tea','tan','ate','nat','bat'])
→ [['eat','tea','ate'], ['tan','nat'], ['bat']]

Note Sorting key: O(n * k log k) where k is max word length. Frequency key alternative: O(n * k) but more code. Interviewers may ask for the optimal approach - mention the frequency-tuple key to avoid k log k sorting per word.

Frequently asked questions

How does Interview Prep handle group anagrams?
Interview Prep covers this with 2 copy-ready snippets on this page. The "Anagram Detection" snippet in Interview Prep uses `Two strings are anagrams if they have identical character frequencies.`.
Which code does the Interview Prep example use?
The "Anagram Detection" snippet uses `Two strings are anagrams if they have identical character frequencies.`, from the Arrays & Strings section of the Interview Prep cheat sheet.
What other Interview Prep snippets are shown for "group anagrams"?
Besides "Anagram Detection", this page also shows "Group Anagrams".
Is there anything to watch out for?
Yes. For "Anagram Detection": Frequency map: O(n) time, O(1) space (bounded by alphabet size). Sorting approach: O(n log n). Always ask: are inputs lowercase only? Unicode? This affects space analysis. Follow-up: find all anagram groups in a list of words.

Browse all tasks by intent