\n In this article, we will enhance our understanding of arrays and lists through algorithm problems and explore various techniques useful when dealing with arrays and lists. Arrays and lists are fundamental and essential parts of data structures, frequently encountered in coding tests. This course will select one algorithm problem and explain the process of solving it step by step.\n <\/p>\n
\n The following is the “Problem of finding a specific number pair in a given array.”\n <\/p>\n
\n Given an integer array \n For example, if \n To solve this problem, several strategies can be considered. The approaches are as follows:\n <\/p>\n \n The second method of using a hash map is more efficient, so let’s use this method to solve the problem. \n Initialize an empty hash map and set up variables to find the sum of two numbers while iterating through the array.\n <\/p>\n \n While checking each number in the array, first check if the complement of the current number exists in the hash map. \n After iterating through all the numbers, if no two numbers are found that sum up to \n Implementing the above approach in code would look like this:\n <\/p>\n \n In the above code, the \n For each number, it calculates the \n The time complexity of this algorithm is O(n), and the space complexity is O(n). \n Arrays and lists are fundamental elements in data processing and play a significant role in various algorithm problems. \n In the future, we will deepen our understanding of data structures such as arrays, lists, and hash maps through various algorithm problems. <\/body><\/p>\n","protected":false},"excerpt":{"rendered":"nums<\/code> and an integer target<\/code>,
\n write a function that returns the indices of the two numbers such that they add up to target<\/code>.\n <\/p>\nnums = [2, 7, 11, 15]<\/code> and target = 9<\/code>,
\n the output should be [0, 1]<\/code>. (2 + 7 = 9)\n <\/p>\nApproach to the Problem<\/h2>\n
\n
target - current number<\/code> exists in the hash map. This has a time complexity of O(n).<\/li>\n<\/ol>\nSolution Method<\/h2>\n
\n First, based on the given array and the target, we will follow these steps:\n <\/p>\nStep 1: Initialization<\/h3>\n
Step 2: Iterate through Numbers<\/h3>\n
\n If it does, return that index as the result. If not, add the current number and its index to the hash map.\n <\/p>\nStep 3: Return the Result<\/h3>\n
target<\/code>, it does not meet the problem’s requirements.\n <\/p>\nCode Implementation<\/h3>\n
\ndef two_sum(nums, target):\n num_map = {}\n for index, num in enumerate(nums):\n complement = target - num\n if complement in num_map:\n return [num_map[complement], index]\n num_map[num] = index\n return []\n <\/code><\/pre>\nCode Explanation<\/h2>\n
two_sum<\/code> function takes two parameters nums<\/code> and target<\/code>.
\n It initializes an empty hash map called num_map<\/code> and iterates through nums<\/code> using the enumerate<\/code> function.\n <\/p>\ncomplement<\/code> and searches for that value in the hash map.
\n If found, it returns a list containing the index of that number and the current index.
\n If not found after checking all, it returns an empty list.\n <\/p>\nComplexity Analysis<\/h2>\n
\n This is due to all numbers and indices stored in the hash map.
\n This method is designed to efficiently find the desired pairs in the given array.\n <\/p>\nConclusion<\/h2>\n
\n In this course, we learned how to efficiently solve the problem of “Two Sum” by exploring array indices and utilizing hash maps.
\n This will help save time and resolve problems in actual coding test situations.\n <\/p>\n
\n With continuous practice and problem-solving, I hope to become a more skilled coder. Thank you.\n <\/p>\n