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Makhabat - Cedar #67
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Makhabat - Cedar #67
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
|
|
@@ -2,18 +2,43 @@ | |
| def grouped_anagrams(strings): | ||
| """ This method will return an array of arrays. | ||
| Each subarray will have strings which are anagrams of each other | ||
| Time Complexity: ? | ||
| Space Complexity: ? | ||
| Time Complexity: O(n) | ||
| Space Complexity: O(n) | ||
| """ | ||
| pass | ||
| hash_table = {} | ||
| for str in strings: | ||
| key = ''.join(sorted(str)) | ||
| if key in hash_table.keys(): | ||
| hash_table[key].append(str) | ||
| else: | ||
| hash_table[key] = [] | ||
| hash_table[key].append(str) | ||
|
|
||
| result = [] | ||
| for key, value in hash_table.items(): | ||
| result.append(value) | ||
| return result | ||
|
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||
| def top_k_frequent_elements(nums, k): | ||
| """ This method will return the k most common elements | ||
| In the case of a tie it will select the first occuring element. | ||
| Time Complexity: ? | ||
| Space Complexity: ? | ||
| Time Complexity: O(n) | ||
| Space Complexity: O(n) | ||
| """ | ||
| pass | ||
| frequency = {} | ||
| for num in nums: | ||
| if num not in frequency: | ||
| frequency[num] = 1 | ||
| else: | ||
| frequency[num] = frequency[num] + 1 | ||
|
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| frequency = dict( | ||
| sorted(frequency.items(), key=lambda x: x[1], reverse=True)) | ||
|
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| result = list(frequency.keys())[:k] | ||
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| return result | ||
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| def valid_sudoku(table): | ||
|
|
@@ -22,8 +47,21 @@ def valid_sudoku(table): | |
| Each element can either be a ".", or a digit 1-9 | ||
| The same digit cannot appear twice or more in the same | ||
| row, column or 3x3 subgrid | ||
| Time Complexity: ? | ||
| Space Complexity: ? | ||
| Time Complexity: O(n^2) | ||
| Space Complexity: O(n) | ||
|
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. These would be accurate answers if we allowed arbitrary boards of nxn (well, actually the space complexity would be O(n^2) too), but since we only accept 3x3 boards, the time and space used will be constant and we can instead say it is O(1) in both time and space. |
||
| """ | ||
| pass | ||
|
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||
| seen = set() | ||
| for i in range(9): | ||
| for j in range(9): | ||
| number = str(table[i][j]) | ||
| if number != '.': | ||
| row = number + 'in row' + str(i) | ||
| col = number + 'in col' + str(j) | ||
| # // for integer | ||
| block = number + 'in block' + str(i//3) + str(j//3) | ||
| if row in seen or col in seen or block in seen: | ||
| return False | ||
| seen.add(row) | ||
| seen.add(col) | ||
| seen.add(block) | ||
| return True | ||
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Don't forget to account for the call to
sortedon line 37, which will take O(n * log(n)) time and thus dominate the O(n) parts of the algorithm. Thus, the correct time complexity here is O(n * log(n)).