Introduction to Python

Python is a general-purpose and high-level programming language. You can use Python to develop GUI applications for desktops, websites and web applications. In addition, Python, as a high-level programming language, allows you to focus on the basic functionality of the application, paying attention to common programming tasks.

Python Libraries

The Python library is a set of functions and methods that allow you to perform many actions without writing your own code. For example, the Python Image Library (PIL) is one of the basic image processing libraries in Python.

Python installers for Windows usually include the entire standard library and often also include many add-ons. For operating systems similar to Unix, Python is generally provided as a set of packages, so it may be necessary to use the filler tools provided with the platform to get several or whole optional components.

Here are some Libraries that can be support for Python,

• Matplotlib
• Pandas
• Requests
• NumPy
• Pyglet

1.Matplotlib

Matplotlib is a Python 2D planning library that produces publication-quality numbers in a variety of print formats and interactive environments on all platforms. Matplotlib can be used in Python scripts, Python and IPython psoriasis, Jupyter laptops, web application servers and four sets of GUI tools.

Matplotlib tries to make things easy and difficult possible. You can create charts, graphs, power spectra, bar charts, error charts, scatter charts, etc., with a few lines of code. For examples, see Graphics templates and Thumbnail gallery.

2. Pandas

Panda is a BSD licensed open-source library that provides high-performance and easy-to-use data structures and data analysis tools for the Python programming language. Pandas is a tool that changes the game when it comes to data analysis using Python and is one of the most preferred and widely used data collection tools, if not the most used.

Key Features of Pandas

• A fast and efficient DataFrame object with the default and custom indexing.
• Tools to load data into data objects in memory from different file formats.
• Data alignment and integrated processing of lost data.
• Remodeling groups and hub history.
• Segments based on large data sets, indexed and mapped.

3. Requests

The request library is the real standard for making HTTP requests in Python. It summarizes the complexities of sending applications through a simple and simple API so that you can concentrate on interacting with the services and data consumption in your application.

4. NumPy

Numpy is the basic library for scientific computing in Python. The object provides a high-performance multidimensional matrix and tools to work with these matrices. If you are already familiar with MATLAB, you can find this tutorial useful to get started in Numpy.

5. Pyglet

Pyglet is a Python programming language library that provides an object-oriented API for creating games and multimedia applications. Pyglet works on Microsoft Windows, Mac OS X Linux; Released under the BSD license.

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