C16/Cedar- Ana Gabriele #39
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chimerror
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chimerror
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Good work!
I left some comments about your time complexity calculation for the anagrams problems, and a few comments about extraneous testing code left in. Otherwise, though, this looks good enough for a Green, so that's what I'm giving it!
| Time Complexity: ? | ||
| Space Complexity: ? | ||
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| Time Complexity: O(m * nlogn) - | python sorting algorithm -> O(n. logn). |
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While this is an accurate answer assuming n stands for the number of characters in the strings and m stands for the number of strings in the list, we can make a simplifying assumption. Since we know the strings are English words, we can be pretty sure they will not get too big in size. On average words in English have about 5 letters, which is going to very quickly get dwarfed by the number of words in the list so we can simply say this is O(m) in time complexity.
| return list(hash_table.values()) | ||
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| print(grouped_anagrams(["eat", "tae", "tea", "eta", "aet", "ate"])) |
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In general, make sure to remove testing code like this before you submit your PRs.
| if len(result) == k: | ||
| return result | ||
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| print(top_k_frequent_elements([9,9,8,8,7],2)) |
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Same thing as above, make sure to remove testing code like this. It helps keep the code cleaner which is good style.
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