Python is an interpreted, high-level, general-purpose programming language.

Python libraries

Why Python?
Python has many open-source libraries and tools that make doing certain tasks and working with data much easier than trying to do them in JavaScript. Luckily, once you learn the basics of one high level programming language, it is not too difficult to code in a new language. Beware of the whitespaces!

NumPy is a library that provides a multidimensional array object, various derived objects (such as masked arrays and matrices), and an assortment of routines for fast operations on arrays, including mathematical, logical, shape manipulation, sorting, selecting, I/O, discrete Fourier transforms, basic linear algebra, basic statistical operations, random simulation and much more. SciPy extends NumPy functionality and provides many other numerical algorithms.

Provides providing fast, flexible, and expressive data structures designed to make working with “relational” or “labeled” data both easy and intuitive. It is suited for tabular data, time series data, arbitrary matrix data, and any other form of observational/statistical data sets.

Used to create 2D graphs and plots. It supports a very wide variety of graphs and plots namely - histogram, bar charts, power spectra, error charts etc. Seaborn is essentially a higher-level API based on the matplotlib library.

A Python module for automation and programmatically controlling the mouse and keyboard.

Build and run your web spiders. Then deploy them to Scrapy Cloud.

An algorithmic trading library for backtesting.

A high-level library for working with neural networks, running on top of the TensorFlow library.

NLTK is a set of libraries, a whole platform for natural language processing.

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Pandas cheat sheet

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Matplotlib cheat sheet

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