Python libraries list

Libraries in Python

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Python libraries list: In this tutorial, you will learn about Python libraries list, python libraries for image processing, python libraries for machine learning and python libraries for data scienc. Python library is a reusable chunk of code that you want to include in your programs. Library loosely describes a collection of core modules. Python module contains build in modules. Python is rich collection of function in software used. Functions related to the domain are grouped inside library and accessed when needed. There are thousands of libraries written by authors. Since library loosely describes collection of core modules. Python standard library is a collection of syntax, token and semantic. A package as library can be installed using a package manager like ruby gems or npm.

matplotlib:- It helps with Data Analyzing and is a numerical plotting library.
Pandas:- It provides fast, expressive & flexible Data structures to easily work with structured & Time Series Data. It is must for data science purpose.
Requests:-It is Python library that lets you send HTTP/1.1 requests, add headers, multipart files, form Data, & parameters with simple Python dictionaries.
Scrapy:-Go for Scrapy, if your motive is fast, high-level screen scraping & web crawling.
Pillow:-It is a friendly fork of Python Imaging Library. If you work with images, it is your best friend.
pywin32: - It provides useful methods & class for interaction with Windows, as the name suggests.
Flask-It is built with a small core and many extensions.
SymPy: -It is an open source library for symbolic Math and is a full fledged CAS (Computer Algebra System) written in Python and it does not need external Libraries.
numPy:- It has advanced Math functions & rudimentary Scientific Computing package.
BeautifulSoup:- It has an excellent HTML and XML parsing library for beginners.
SciPy:- SciPy has a number of user friendly & efficient numerical routines, it includes routines for optimization & numerical integration.
PyGTK:- It lets you easily create programs with a Graphical User Interface with Python. Following are applications where python libraries are used.

Python library for Machine Learning:-

“Machine Learning is the field of study that gives computers the ability to learn without being explicitly programmed.”
They are typically used to solve various types of day to day life problems. In previous times Machine learning task was performed by manually coding all algorithms and formulas.
This process was too time consuming, tedious and inefficient. But nowadays it became easy because of Python libraries, frameworks and modules.
Today python is most popular programming language for machine learning and has vast collection of libraries.
All the libraries play an important role in Machine learning of python programming.
NumPy is a very popular python library for large multi-dimensional array and matrix processing, with the help of a large collection of high-level mathematical functions.
SciPy library is used in Machine Learning enthusiasts as it contains modules for optimization, linear algebra, integration and statistics.

Python library for Image Processing :-

The data, images are present in today’s world. Before using them they must be processed, analyzed to improve quality.
Common image processing steps are cropping, flipping, etc.
Python plays an important role of image processing task as a programming language and is growing rapidly.
Python is growing rapidly as programming language and free availability of many state of art image processing tool is in the ecosystem.
Numpy is the best library for image processing here and provides support for arrarys.Also other libraries also plays an important role for image processing.

Python library for Data Science:-

Python is an easy-to-learn, easy-to-debug, widely used, object-oriented, open-source, high-performance language, and there are many benefits to use Python programming.
Python is built with python libraries that are used by programmer’s everyday to solve problems.
There are libraries that give us functionality of data.
Python is best language for statics, ML and predictive analysis tasks.
Below we will explain how library work as data science.
Numpy is numerical python it contains basic linear functions.
Pandas are structured data operations and manipulators.
Matplotlib used for plotting vast variety of graphs, starting from histograms to line plots to heat plots and used it for dimensionality reduction and feature extraction.

Python library for Web Scraping:-

If we want to large amount of data from website quickly .How will do it manually without going to every website. So web scraping plays an important role.

The term web scraping is used to describe the use of program or algorithm to extract large amount of data from websites.
Web page scraping can be done using multiple tools or frameworks in Python.
There is variety of options available for scraping data from a web page, each has different needs.
The difference between web-scraping and web-crawling. Web crawling is used to index the information on the page using bots also known as Crawlers and Web-scraping is an automated way of extracting the information using bots also known as Scrapers.
Following are some tools required for web scraping:-