Space - Diana #19
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Space - Diana #19
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CheezItMan
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Sep 16, 2020
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| # Time Complexity: O(n) | ||
| # Space Complexity: O(1) | ||
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| def grouped_anagrams(strings) |
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👍 , however you have O(n) space complexity.
| array_num_hash = num_hash.to_a | ||
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| # sort by occurences | ||
| sorted_array_num_hash = array_num_hash.sort_by {|num| -num[1]} |
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just noting this is an O(n log n) operation.
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| # Time Complexity: O(n^2) in worst case because of the sorting to be done | ||
| # Space Complexity: O(1) | ||
| def top_k_frequent_elements(list, k) |
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You have an O(n log n) time complexity algorithm which is pretty good and O(n) space complexity because you're making a hash and an array both proportional to the size of the original list.
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Hash Table Practice
Congratulations! You're submitting your assignment!
Comprehension Questions
- Hash values are uniformly distributed
- Keys that are close have hash values that are far apart
- Hashing appears to be random