TOP PYTHON LIBRARIES TO LEARN IN 2022

Introduction

Due to the huge number of libraries,?Python?is used seamlessly for the trending technologies like Artificial intelligence, web development, scripting, game development, and much more. Because of its rapid growth in advanced technologies, the popularity of python is drastically increased in the past few years. In this article, the top Python libraries are mentioned that are in trend among the developers.

To begin with, lets us understand what a Library & Python library is,

Library

A library refers to a collection of pre-written code like files, programs, routines, scripts, functions, classes that can beimport to our project for adding specific functionality. Libraries help us to use thepre-written code without writing the code from the scratch to enhance the functionality implemented by our code.

Python Library

Python offers a large number of python libraries with pre-compiled code that is used for the different types of development, ranging from web development to machine learning. Python Standard Library plays a very important role which consists of more than 200 core modules. It makes python coding simpler and convenient for the developers along with its simple syntax to implement complex projects. Let’s take a look at the list of the most popular Python libraries used in different development areas.

Pandas

Pandas stands for ‘Python Data Analysis Library’. Pandas is an important data analysis library used for data science applications.

Python is an open-source library that provides high performance among the most famous python libraries. This Library provides flexible data structure to work with structured data like tabular, multidimensional heterogeneous datas and time series data. It support data science operations like Sorting, Iteration, Concatenation, data conversion, Visualizations, Aggregations, etc. It is simple, fast, and expressive among other data analysis libraries and they are:

• Numpy
• SciPy
• Cython

Features of Pandas

• Easy to learn and use offering high performance and provides Time Series functionality.
• It has many built-in methods with graphical interface used for reshaping and pivoting of the data sets.
• It is used for data alignment, integration of the missing data and aggregations, transformations.
• Process different formats of data sets like matrix data, tabular heterogeneous, time series and its operations such as sub setting, slicing, filtering, group By, re-ordering, and re-shaping.

NumPy

NumPy stands for ‘Numerical Python’. NumPy is a popular Machine learning library with advanced math functions and a rudimentary scientific computing package.

NumPy is also one of the famous Python libraries which provide most basic Data Structures, multidimensional array objects and a collection of routines for processing of array. It consists of in-built mathematical functions, logical operations for easy computations. It has in-built functions for linear algebra and random number generation. The most important object defined in NumPy is an N-dimensional array type called ndarray.

Features of NumPy

• It provides many mathematical functionalities with useful linear algebra, Fourier transform, and random number capabilities.
• It is easy to learn and use with good documentation.
• Sophisticated functions and can be used in Data Science.
• It is used for scientific purpose with Tools for integrating C/C++ and Fortran code.

SciPy

SciPy stands for ‘Scientific Python’. Among many libraries for data science, SciPy is the simplest library with many mathematical algorithms that are ideal for solving statistics problems.

SciPy is an open-source library used for high-level scientific computations solving mathematical, scientific, engineering, and technical problems. It is similar to NumPy to handle complex computations which heals with large number of data and stats. It works with Numpy allows sorting and indexing of array data, the numerical data code is stored in SciPy. It is an open-source library with huge community support commonly used by developers.

Features of SciPy

• Large community support with many built in scientific constants.
• Rapid development with data science tools.
• Easy to get started with different data structures like graph, matrix.

Tensor Flow

Tensor Flow is the most popular library that is used for implementing machine learning and deep learning applications. Tensor Flow is an open source machine learning framework for all developers developed by Google team to build their AI models.

Tensor Flow can store an algorithm in a cube and array-like structure and perform a tensor operation on them. Even in neural computation, developers use Tensor Flow because it is very good with the new algorithms.

Tensor Flow Features

• It is an open-source library. With Tensor Flow, we can develop ML models easily because it uses high-level APIs.
• It can create ML models for different ………………..?click the below link to read the remaining blog contents.

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