Move two_sum to hash table folder

data_structures/arrays/two_sum.rb

@@ -86,48 +86,3 @@ print(two_sum([3, 2, 4], 6))
 
 print(two_sum([3, 3], 6))
 # => [0,1]
-
-#
-# Approach 3: Using a Hash
-#
-
-# Complexity analysis
-
-# Time complexity: O(n). We traverse the list containing n elements exactly twice.
-# Since the hash table reduces the lookup time to O(1), the time complexity is O(n).
-
-# Space complexity: O(n). The extra space required depends on the number of items
-# stored in the hash table, which stores exactly n elements.
-
-def two_sum(nums, target)
-  hash = {}
-
-  # create a hash to store values and their indices
-  nums.each_with_index do |num, i|
-    hash[num] = i
-  end
-
-  # iterate over nums array to find the target (difference between sum target and num)
-  nums.each_with_index do |num, i|
-    difference_target = target - num
-
-    if hash[difference_target] && hash[difference_target] != i
-      return [i, hash[difference_target]]
-    end
-  end
-end
-
-nums = [2, 7, 11, 15]
-target = 9
-print(two_sum(nums, target))
-# => [0,1]
-
-nums = [3, 2, 4]
-target = 6
-print(two_sum(nums, target))
-# => [1,2]
-
-nums = [3, 3]
-target = 6
-print(two_sum(nums, target))
-# => [0,1]

data_structures/hash_table/two_sum.rb

@@ -0,0 +1,70 @@
+# Challenge name: Two Sum
+#
+# Given an array of integers nums and an integer target, return indices of the two numbers such that they add up to target.
+#
+# You may assume that each input would have exactly one solution, and you may not use the same element twice.
+#
+# You can return the answer in any order.
+#
+#
+# Examples
+#
+# Input: nums = [2, 7, 11, 15], target = 9
+# Output: [0,1]
+# Explanation: Because nums[0] + nums[1] == 9, we return [0, 1].
+#
+# Input: nums = [3, 2, 4], target = 6
+# Output: [1,2]
+#
+# Input: nums = [3, 3], target = 6
+# Output: [0,1]
+# Explanation: Because nums[0] + nums[1] == 9, we return [0, 1].
+#
+# @param {Integer[]} nums
+# @param {Integer} target
+# @return {Integer[]}
+
+#
+# Approach: Using Hash table
+#
+
+# Complexity analysis
+
+# Time complexity: O(n). We traverse the list containing n elements exactly twice.
+# Since the hash table reduces the lookup time to O(1), the time complexity is O(n).
+
+# Space complexity: O(n). The extra space required depends on the number of items
+# stored in the hash table, which stores exactly n elements.
+
+def two_sum(nums, target)
+  hash = {}
+
+  # create a hash to store values and their indices
+  nums.each_with_index do |num, i|
+    hash[num] = i
+  end
+
+  # iterate over nums array to find the target (difference between sum target and num)
+  nums.each_with_index do |num, i|
+    difference_target = target - num
+
+    if hash[difference_target] && hash[difference_target] != i
+      return [i, hash[difference_target]]
+    end
+  end
+end
+
+nums = [2, 7, 11, 15]
+target = 9
+print(two_sum(nums, target))
+# => [0,1]
+
+nums = [3, 2, 4]
+target = 6
+print(two_sum(nums, target))
+# => [1,2]
+
+nums = [3, 3]
+target = 6
+print(two_sum(nums, target))
+# => [0,1]