Data Structure
Data structures are different ways of storing data on a computer. Data structures are introduced as different ways of organizing and storing data on a computer. Organized data improves efficiency and performance. The choice of data structure affects the performance of software or application. Choosing the proper data structure is crucial for optimal software performance. Big companies like Google, Apple, Amazon, and Facebook ask questions about data structures and algorithms from their candidates during the interview process. A professional software developer must know which data structure to choose for a particular app, which directly affects the performance.
Some Examples of Data Structure
Suppose you were given a bunch of wood and wanted to choose black wood. But the woods are not organized, so it is difficult to pick the black wood, and also, it is time-consuming. But what if we arrange the wood in a sequence? Then choosing the black woods would be easier and less time-consuming.
Let's look at another example suppose there are a bunch of people who want a ticket for a concert. It becomes almost impossible to get ticket if the people aren't organized in a queue. And this is called a queue data structure.
And finally, suppose there are a bunch of books on the table, and you want to return them to the library without putting them in an organized way. It isn't easy to carry them. So if we put them in an organized manner, it becomes easier to take them. It reminds us of the stack data structure. There are many types of data structures, each with advantages and disadvantages.
Algorithm
An algorithm is a set of instructions that must be carried out in a specific order to produce a desired result. Algorithms are used in everyday life and in computer science to solve problems and perform tasks. Good algorithms solve problems correctly and efficiently. Algorithms are used to write time and memory efficient programs. The efficiency and performance of a program depend on the choice of algorithm. Different types of algorithms are used by famous companies to transmit live video, find the shortest path on a map, and arrange solar panels on the International Space Station. Good algorithms solve problems correctly and efficiently.
Example of Algorithm
So let's look at the previous example we gave for the data structure in which we organize wooden items. We have to accomplish several steps if we want these wood items for flooring. The first step would be to choose flooring and which colour we will use. Then we need to purchase it and bring it home. The third step is we need to prepare some flooring. The next step is to determine the layout of the flooring in the space. And final step is we need to trim the door chasing, and our floor is ready. So to complete a task, we are performing some steps. This set of instructions, this set of steps, is called an algorithm.
Importance of Data Structure and Algorithm
The efficiency and performance of a program depend on the choice of data structure and algorithm. Companies ask questions related to data structures and algorithms during the interview process to evaluate a candidate's problem-solving ability and fundamental concepts of programming. Data structures and algorithms are used in everyday life and in computer science to solve problems and perform tasks. Learning about data structures and algorithms allows us to write time and memory efficient programs.
In the third example of data structure, we saw an example of books; it will always be impossible to find the book we need if it isn't organized. This is how a librarian efficiently manages it in a particular form to perform a task on it. Here, books are the data and arranging them like this is a data structure and finding the book we need is an algorithm. Thus, we can easily see the essential data structures and algorithms.
Types of Data Structure
There are different types of data structures in Python, which can be classified as primitive or non-primitive. Primitive data structures include integers, floats, strings, and Booleans, while non-primitive data structures include lists, tuples, arrays, dictionaries, sets, linked lists, stacks, queues, trees, graphs, and hashmaps. Linear data structures are arranged in a sequential order, while non-linear data structures are not. Built-in data structures are included in Python, while user-defined data structures are created by users. The choice of data structure depends on the specific task and its efficiency and performance.
Types Of Algorithms
There are different types of algorithms in Python, that includes sorting, searching, graph, dynamic programming, divide and conquer, and recursive algorithms.
- Sorting algorithms arrange data in ascending or descending order.
- Searching algorithms find a specific value in a data set.
- Graph algorithms work with data represented as a graph.
- Dynamic programming algorithms solve problems by breaking them down into smaller subproblems.
- Divide and conquer algorithms solve problems by breaking them down into smaller subproblems and combining the results.
- Recursive algorithms solve problems by breaking them down into smaller subproblems of a similar nature.
- Different types of algorithms have unique properties that work efficiently in different circumstances.
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