**Logic:** Anagrams = same char counts. **Approach:** Group by sorted string or char-frequency tuple. **Python:** `groups = defaultdict(list); [groups[tuple(sorted(Counter(s).items()))].append(s) for s in words]`. O(n·k log k) for n words, k max length. **Alternative:** Sort...
Pro-Move: Unicode normalization for i18n. Red Flag: O(n²) pairwise compare.
This easy-level Python/Coding question appears frequently in data engineering interviews at companies like Paytm. While less common, it tests deeper understanding that distinguishes strong candidates. Mastering the underlying concepts (python) will help you answer variations of this question confidently.
Start by clearly defining the core concept being asked about. Interviewers want to see that you understand the fundamentals before diving into implementation details. Structure your answer with a definition, then explain the practical application with a concise example.
Logic: Anagrams = same char counts. Approach: Group by sorted string or char-frequency tuple. Python: groups = defaultdict(list); [groups[tuple(sorted(Counter(s).items()))].append(s) for s in words]. O(n·k log k) for n words, k max length. Alternative: Sort each as key. Why: Deduplication, fuzzy matching. Production: Handle case, unicode.
Want feedback on your answer?
Paste your answer to this question and our AI Coach scores it, finds gaps, and shows you the FAANG-level version.
Paste your answer and get instant AI feedback with a FAANG-level improved version.
Analyze My Answer — FreeAccording to DataEngPrep.tech, this is one of the most frequently asked Python/Coding interview questions, reported at 1 company. DataEngPrep.tech maintains a curated database of 1,863+ real data engineering interview questions across 7 categories, verified by industry professionals.