Sorting means a sorted order of the data. Often, our data is unsorted, which means we need a way to sort it. Usually, sorting is done by comparing different elements with each other and coming up with the ranking. In most cases, without the comparison, we cannot decide on the sorting part. After the comparison, we also need to swap the elements so that we can reorder them. A good sorting algorithm has the characteristics of making a minimum number of comparisons and swapping. There is also non-comparison based sorting, where no comparison is required to sort a list of items. We will also explore those algorithms in this chapter.

Sorting can be classified into different types based on the type of data set, direction, computational complexities, memory usage, space usage, and so on. Here are few of the sorting algorithms we will explore in this chapter:

• Bubble sort
• Insertion sort
• Selection sort
• Quick sort
• Merge sort
• Bucket sort

We will keep our discussion limited to the preceding list, as they are the most commonly used sorting algorithms and can be grouped and classified under different criteria such as simple sorting, efficient sorting, distribution sorting, and so on. We will now explore each of the sorting functionalities, their implementations, and complexity analysis, along with their pros and cons. Let's get started with the most commonly used sorting algorithm - bubble sort.