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CheezItMan
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Mar 12, 2020
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| # Time Complexity: O(n * m) where n is the number of characters in the longest word and m is the size of the input array | ||
| # It might actually simplify to just O(n) where n is the total number of input charcters, because you're only sorting each word once | ||
| # Space Complexity: O(n) where n is the size of the input array | ||
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| def grouped_anagrams(strings) |
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👍 You are right on time complexity except that it would be better said that time complexity is O(n) if the words are guaranteed to be less than a certain length.
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| # Time Complexity: O(n) where n is the size of the array | ||
| # Space Complexity: O(n) where n is the size of the array | ||
| def top_k_frequent_elements(list, k) |
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Yes, but you are sorting all the values so this is worst case O(n log n)
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