Top 15 Python Libraries You Must Know In 2022

Author

Ruchir Kakkad

06 Jan 2022

14 min

Python libraries are a fundamental tool to consolidate the training of every web programmer. Did you know that programs developed with Python are the most important in the digital world? Yes, Python is one of the most used programming languages, and many companies need to have it.

If you want to become the professional all organisations seek, you must learn everything about the Python language. Therefore, discovering the most used Python libraries will allow you to develop all kinds of mobile apps, responsive web pages and even organise information like a professional.

So, to continue expanding your knowledge on this topic, today, you will learn what Python libraries are, what the main Python libraries are, and how you can install them on your computer in simple steps.

Okay, are you ready to find out all about Python libraries? Let’s get started!

What are Python libraries?

Before knowing which Python libraries are most used, we consider it essential to know precisely what Python libraries are.

According to David Zarruk, professor of the Predictive Analytics and Regression Models in Python course, a programming library is a set of functions that someone wrote somewhere in the world and has made available for free to anyone.

So what is a library in Python? This concept refers to the set of functional implements that will help you code this entire programming language to create an independent interface.

Python libraries are extensive and have a large number of content productions. They consist of various modules that allow access to specific system functionalities such as file input and output, standardized solutions to programming problems, etc.

Also, depending on the operating system you have, you can get different functions from each Python library. For example, the complete standard library is included along with additional components for the Windows system.

A plus for Python libraries is that they have a collection of components such as individual programs, modules, packages, frameworks, applications, and more functions that you can find in the Python Package Index.

What are the types of Python libraries that exist?

Python libraries can be used for many areas of programming since each system has different processes that need a specific library to solve various functions.

Next, we present some types of programming libraries so that you can choose the one that best suits your needs.

  • Visualization: ideal for better understanding the data and understanding any problems that may arise.
  • Numerical Calculation: the most suitable for preparing data and calculating relevant attributes.
  • Machine Learning: They focus on processing information and solving data classification and regression problems.
  • Deep Learning: oriented towards predicting data from a broad set of information.
  • Explainable Artificial Intelligence: they apply technological methods and techniques that use artificial intelligence to provide efficient results.
  • Natural Language Processing: use the Calculation of normalized frequencies to build models with text data.

As you can see, according to the type of work you are going to do, you should select the Python library that best suits your objectives since not all of them will help you to complete the same activities efficiently.

What are the best Python libraries?

Now yes! You have reached the section where you will find all the information you were waiting for. Keep in mind that each of them is used for specific purposes, as we mentioned above.

So, without further ado, let’s go straight to the most used Python libraries so far, which you must know so that your programming levels rise this 2022.

By the way, all these Python libraries are free!

MatplotlibThis is one of the most used Python libraries, as its processing and graphics generator are of high quality. In addition, it gives you the facility to publish this data both physically, underprint, and digitally.

It uses 2D paths and many types of graphics created with just a few lines of code. Examples are histograms, bar charts, power spectra, time series, error diagrams, etc.

Seaborn

Seaborn is a Python graphical library specialized in the visualization of statistical data. Among its main characteristics, we can highlight its high-level interface, which is attractive and very interactive.

This aspect is essential when it comes time to clarify the data after analysis, making their visualization easier. It is also compatible with other Python libraries such as Pandas and Matplotlib.

Bokeh

One of the Python libraries will help you visualize the data from a more interactive perspective within a web browser. In addition, you can create elegant and versatile graphics with data that arrives in real-time, thanks to its well-performing developers.

NumPy

Numpy allows you to create a universal data structure to facilitate its analysis and interchange of various algorithms of all the Python libraries.

Like many Python libraries, it implements multidimensional vectors and matrices that store a large number. In turn, it has high-level mathematical functions and uses various data structures.

SciPy

On the other hand, SciPy is a python library specialized in numerical Calculation and data analysis, as it allows you to create numerical routines with data structures. In addition, it is easy to use and operate and incorporates the following functions: optimization, numerical integration, linear algebra, statistics, Fourier transforms, etc.

Best of all, according to the SciPy official website,, this is a very accessible and productive Python library for programmers of any training or level of experience. Therefore, we are sure that it will be easy for you to get used to it and take advantage of all the benefits it offers you. 

Pandas

If you are looking for a Python library focused on scientific data, Pandas is one of the most useful you will find. Its main functions are Data Series and the Data Frame for two dimensions.

Additionally, it is very easy to use to manipulate data and is used in finance, social sciences, statistics, and engineering.

Numba

Numba is a programming library that translates functions optimized thanks to the LLVM industrial standard; its numerical algorithms reach a very high speed in its execution, and, to use it, you don’t need to have a C / CC ++ compiler.

This tool takes care of all the optimization of functions. However, you will need to apply one of Numba’s decorators to automate the sequence.

Scikit-Learn

This Python library has Machine Learning and data analysis functions. Thanks to its multiple machine learning techniques, it is a very easy-to-use tool.

You can use Stickit-Learn to solve classification and regression problems, such as support vector machines, decision trees, linear and polynomial regression, clustering, dimensionality reduction, etc. Its interface is simple and consistent, as it can be modelled with just one line of code.

TensorFlow

It is part of the Python libraries that Google developed. It allows you to perform numerical calculations thanks to data flow diagrams and for various scientific calculation applications such as Deep Learning.

According to the official website of TensorFlow, this is an open-source platform for machine learning that has a comprehensive and flexible ecosystem of tools, libraries, and resources, which allows researchers to innovate with machine learning and developers to create applications. with AA technology easily”.

Keras

Thanks to neural networks, this Python library has a high-level interface that is very easy to use. Although it shares similar functions to other Python libraries, such as TensorFlow and CNTK, this particular library can calculate if an idea will have good results.

PyTorch

PyTorch was developed by Facebook and will help you obtain an efficient numerical calculation in CPU and GPU codes. Thanks to its graphics cards, it is a programming library that can execute your code much faster.

In addition to using matrix calculations and massive derivatives, it also uses deep learning, known as Deep Learning to process all kinds of information.

SHAP
It is a Python library that works with Explainable Artificial Intelligence. It is part of Machine Learning techniques since it performs calculations in the theoretical field of games to determine the variables with the most influence on its predictions.

Like several Python libraries, SHAP helps you understand decisions in neural network models, both individually and globally.

NLTK

Also known as Natural Language Toolkit for its acronym in English, it is one of the oldest Python libraries used today, thanks to its efficiency in processing tasks.

It incorporates stemming, tokenization, stopword exclusion, and much more. This is one of the Python libraries most used as a study and teaching tool.

Gensim

It is characterized by being a natural language Python library. Gensim’s most significant differential is theme modelling, as it can automatically identify the background of a set of documents.

In addition, you can import vector presentations and build similarity analyses when searching.

SpaCy

SpaCy is also a natural processing Python library, but it has a much more differentiating feature: it is the fastest library on the market.

In addition, it allows you to send, trace and dissect network packets. You can build tools to probe, scan and attack networks. It also works with machine learning tasks.

Pillow

If you are a programmer who works with images of all the Python libraries that we have mentioned, this may be one of the most suitable for you.

This specialized imaging Python library provides impressive results for good file format support and highly efficient image processing capabilities.

Scrapy 

On the other hand, we have this collaborative and open-source platform to extract all the data you need from websites quickly and easily. This Python library offers you extensible functionalities to connect all the functions you want to add to your project.

How to install the Python libraries?

Now that you know which are the most used Python libraries, you probably wonder how to import Python libraries to your computer. Do not worry. In this section, we will get you out of your doubts.

Next, you will discover step by step what is the process to install Python libraries with the use of the “pip” module and the “.main ()” method.

Ready? Let us begin!

Find the Scripts and Pip files before starting the operation; you must ensure that you have the Python 3.7 version. Otherwise, you will not find the folders that we will mention below.

Go to the Python folder and click on “Scripts” inside. There, you will find several system modules, but we are only interested in opening the one called “pip.”

Copy the address path

Inside the “pip” file, you will find a code, which you must paste into the cmd of the system you have. Once this step is done, enter the command “pip install” with the name of the library or module you want to install.

Execute the order

Once the order to install “pip” has been placed, the installation will begin. If you have followed all the steps in the order indicated, you will not have any problems.

Ready! You already know how to install any Python libraries on your computer, with free access for future projects.

Congratulations! Now you know the most used Python libraries, and you are ready to continue your path as a web programmer successfully.

All the Python libraries mentioned are highly recommended and easy to use. In addition, they give you many benefits and functionalities in their use, at the same time that they optimize the processes that you want to implement. Therefore, using them in your following projects will greatly complement your work and obtain better results.

Remember that the world of Python does not end here, and if you want to be a successful professional, you must always keep learning. To do this, we recommend that you continue to discover more about this topic with the Python intermediate online course: functions and algorithms.

Also, do not forget to review our catalogue of web development and technology courses to learn about similar topics that, in the same way, will enhance your CV.

Good luck!

 

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