Whether you just entered the programming world or have experience in the field, who would not like a collection of codes that make things easier for them? These code collections are called libraries which serve as a stress buster for programmers as they let them avoid writing repetitive codes.
In this article, we are about to reveal the top 5 Python libraries every programmer should know regardless of their experience. So, if you are looking for a way that can make things a little bit easier while writing the codes, keep on reading.
1. NumPy
Founded in 2005 by Travis Oliphant, Numpy makes its place in the top 5 libraries with more than 32 million downloads across the globe. Whether you want to do numerical computing or handle large, multi-dimensional arrays and matrices, this library has got you covered.
Its key features are operations on arrays, mathematical functions, linear algebra, and random number generation. If you are in search of a library that helps you in data manipulation and analyses then Numpy should be on your priority list.
2. Pandas
Wes McKinney introduced Panda in 2008. He combined panel data and Python data analysis and named it “Panda”. Besides the purpose is the same as Numpy– data manipulation and analyses, it is distinguished due to its features.
It has features like data structures like DataFrame for tabular data, and tools for reading and writing data as it makes things much easier and more efficient for programmers. It is known for various reasons including its capability of simplifying the cleaning process, exploring, and analyzing data.
3. Matplotlib
Founding member of NumFOCUS, John D. Hunter is the maker of Matplotlib. He founded it in 2002 with a vision to make data visualization easier for programmers. A good Python assignment helper who specializes in data visualization would recommend Matplotlib as its key features are impressive.
It helps programmers in Plotting 2D and basic 3D graphs, creating a variety of charts and plots. Every programmer needs to know about Matplotlib as it provides a flexible and customizable way to create high-quality visualizations.
4. Scikit-learn
Machine learning and data mining hold significant importance in the programming world. In 2007, David Cournapeau thought to make things easier for programmers and introduced Scikit-learn.
A Fun fact about it is that it is built on NumPy and Matplotlib. It is said to be beginner-friendly for implementing machine learning algorithms which makes things easier for programmers to experiment with and understand various techniques.
5. Requests
While it was initially released in 2011, it was only in 2023 that it became stable with the purpose of HTTP requests and web scraping. It simplifies the process of sending an HTTP request, handling cookies, and working with web APIs.
If you ask why it makes its place in the top 5 libraries, try fetching information from the internet with its help and you will not ask this question again. It is an essential tool for web development and data retrieval.
Final Thought
No matter if you are entering the field or have years of experience, these libraries can save you time by providing effective solutions. Choose any of the libraries mentioned in this article according to your needs and use. Once you have chosen the library, gain hands-on experience in it and master it so you can make a good place in the world of programming.