I mentioned in yesterday’s post that a lot of data manipulation involves lists, nested and otherwise. Another common task is sorting elements in a list. Day 6 of 30 Days of Algorithms is a Merge Sort, which is another “divide-and-conquer” algorithm.

Managing data almost always involves working with hierarchical or nested data. Whether we are talking about nested files and folders, product categories and sub-categories, music, … you name it. But we store data in a database in a flat structure. This makes sense because the data objects themselves share the same attributes and it makes for easy searching. But how we store the data and how we need to visualize and manipulate it don’t necessarily match. So how do we efficiently transform a flat array to a tree? Day 5 of 30 Days of Algorithms will present one solution with O(n) complexity.

Given two lists of elements, how do you find which items appear in both lists? The algorithm for Day 4 of 30 Days of Algorithms demonstrates how to find the overlap of two lists (list intersection).

Our algorithm for Day 3 of 30 Days of Algorithms is a Bubble Sort. Bubble Sort is not an efficient sort algorithm (The Big-O notation for the time complexity is 0n²) but it is useful for learning. The basic premise is very simple : Start with the first two items in the list. If the first item (left) is higher than the second item (right), swap them.

The algorithm for Day 2 of 30 Days of Algorithms is a useful formula to find a missing number in an array of numbers from 1 – N. This algorithm only works if there is one-and-only-one missing number, and no duplicate numbers. There are other algorithms for those cases which I will cover on a different day.