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| 1 | +// Guided approach |
| 2 | +// TC : O(n*k), where n is the number of strings, and k is the average length of each string. |
| 3 | +// SC : O(n*k) |
| 4 | +// overal time complexity improved : from O(n * klogk) to O(n * k) |
| 5 | + |
| 6 | +/** |
| 7 | + * Time Complexity Breakdown: |
| 8 | + * |
| 9 | + * Step | Time Complexity | Explanation |
| 10 | + * --------------------------------------- | ------------------- | ---------------------------------------- |
| 11 | + * Outer loop over strings (`for` loop) | O(n) | Iterate over each string in the input array `strs`. |
| 12 | + * Create key (`createKey`) | O(k) per string | For each string, count character frequencies, with k being the length of the string. |
| 13 | + * Map operations (`set` and `get`) | O(1) per string | Inserting and retrieving values from a Map. |
| 14 | + * Result array | O(n * k) | Storing grouped anagrams in the result array. |
| 15 | + * |
| 16 | + * Overall Time Complexity: | O(n * k) | Total time complexity considering all steps. |
| 17 | + * |
| 18 | + * Space Complexity Breakdown: |
| 19 | + * |
| 20 | + * Step | Space Complexity | Explanation |
| 21 | + * --------------------------------------- | ------------------- | ----------------------------------------- |
| 22 | + * Map to store grouped anagrams | O(n * k) | Map stores n groups with each group having at most k characters. |
| 23 | + * Auxiliary space for `createKey` | O(1) | The frequency array used to count characters (constant size of 26). |
| 24 | + * Space for the result array | O(n * k) | Result array storing n groups of up to k elements. |
| 25 | + * |
| 26 | + * Overall Space Complexity: | O(n * k) | Total space complexity considering all storage. |
| 27 | + */ |
| 28 | + |
| 29 | +/** |
| 30 | + * @param {string[]} strs |
| 31 | + * @return {string[][]} |
| 32 | + */ |
| 33 | + |
| 34 | +var groupAnagrams = function (strs) { |
| 35 | + const createKey = (str) => { |
| 36 | + const arr = new Array(26).fill(0); |
| 37 | + |
| 38 | + for (const ch of str) { |
| 39 | + const idx = ch.charCodeAt() - "a".charCodeAt(); |
| 40 | + arr[idx] += 1; |
| 41 | + } |
| 42 | + |
| 43 | + return arr.join("#"); |
| 44 | + }; |
| 45 | + |
| 46 | + let map = new Map(); |
| 47 | + |
| 48 | + for (const str of strs) { |
| 49 | + const key = createKey(str); |
| 50 | + map.set(key, [...(map.get(key) || []), str]); |
| 51 | + } |
| 52 | + |
| 53 | + return Array.from(map.values(map)); |
| 54 | +}; |
| 55 | + |
| 56 | +// *My own approach |
| 57 | + |
| 58 | +// Time Complexity |
| 59 | +// 1. Sorting Each String: |
| 60 | +// Sorting a string takes O(k*logk), where k is the length of the string. |
| 61 | +// Since we sort each string in the input array of size n, the total cost for sorting is O(n*klogk). |
| 62 | + |
| 63 | +// 2. Hash Map Operations: |
| 64 | +// Inserting into the hash map is O(1) on average. Over n strings, the cost remains O(n). |
| 65 | + |
| 66 | +// Overall Time Complexity: |
| 67 | +// O(n*klogk), where n is the number of strings and k is the average length of a string. |
| 68 | + |
| 69 | +// /** |
| 70 | +// * @param {string[]} strs |
| 71 | +// * @return {string[][]} |
| 72 | +// */ |
| 73 | + |
| 74 | +// var groupAnagrams = function (strs) { |
| 75 | +// // helper function |
| 76 | +// const sorted = (str) => { |
| 77 | +// return str.split("").sort().join(""); |
| 78 | +// }; |
| 79 | + |
| 80 | +// let obj = {}; |
| 81 | + |
| 82 | +// for (const str of strs) { |
| 83 | +// const key = sorted(str); |
| 84 | +// obj[key] = [...(obj[key] || []), str]; |
| 85 | +// } |
| 86 | + |
| 87 | +// return Object.values(obj); |
| 88 | +// }; |
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