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Nice work Nora, you hit the learning goals here. Check out my small comments on time complexity. Well done.
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| # Time Complexity: O(n^2) or O(m * n) where m is the number of words and n is the characters | ||
| # Space Complexity: O(n) where n is the number of words in the array | ||
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| def grouped_anagrams(strings) |
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You are right that it's O(nm) which isn't O(n^2) unless n and m are the same. On the other hand if the words are all relatively small (like English words, you can call this O(n).
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| # in the case of a tie it will select the first occurring element. | ||
| # Time Complexity: O (n log n) due to sort_by / quick sort - best case. Worst case is O(n^2) if the data is already ordered | ||
| # Space Complexity: O(n) | ||
| def top_k_frequent_elements(list, k) |
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👍 , although since Ruby uses MergeSort, this is always O(n log n)
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Hash Table Practice
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