In this tutorial, we will study **Sorting in Data Structures**.

- Sorting is a process of arranging the data in a particular order.
Arranging a set of data in some kind of order is referred as sorting.__Definition:__- In sorting data is arranged in ascending or descending order.

**Example:**

Telephone directory names of persons arranged in alphabetical order.

Consider a simple example of sorting, We are having 5 random numbers as **10 2 19 1 8. **As these are the random number we need to sort the number as, **1 2 8 10 19**

We got the sorted list easily but how we sort these random numbers to be sorted. For this, there are various techniques available in a data structure which are different from each other and performed in the different fashion to arrange the data in particular order.

## Different techniques of Sorting in Data Structures

As above we are having different techniques for sorting these techniques has different **time** **complexity**.

## Time complexity

The total time required for execution of a program is known as time complexity.

We will choose anyone sorting technique whose complexity will be suitable for your needs or we use sorting technique which is efficient.

## Advantages of sorting

- It will make retrieving and traversing data easy and simple.
- It makes memory management easy.
- Sorting also makes searching easy.

## Sorting algorithms complexity

Sorting Technique | Best case | Average case | Worst case |
---|---|---|---|

Bubble | O(n) | O(n^{2}) |
O(n^{2}) |

Insertion | O(n) | O(n^{2}) |
O(n^{2}) |

Selection | O(n^{2}) |
O(n) | O(n) |

Quick | O(n^{2}) |
O(n log n) | O(n log n) |

Merge | O(n log n) | O(n log n) | O(n log n) |

Binary | O(n log n) | O(n log n) | O(n^{2}) |

Radix | O(n^{2}) |
O(n log n) | O(n log n) |

Hip | O(n log n) | O(n log n) | O(n log n) |

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