These are my go-to libraries for Python data crunching.

Every Python developer knows some or all of these libraries, because they’re stable, reliable, and excellent at what they do.

Jupyter Notebook is a tool to run and write Python code easily, showing results right away, and allowing you to combine code, charts, notes, and files in one place. You can start Jupyter Notebook ...

This is a collection of exercises that have been collected in the numpy mailing list, on stack overflow and in the numpy documentation. The goal of this collection is to offer a quick reference for ...

Abstract: Raspberry Pi (RPi) is a well-known single-board computer natively equipped with a Linux-based operating system, Raspbian, and a powerful programming language, Python. In this article, we ...

So, you’re playing with ML models and you encounter this “One hot encoding” term all over the place. You see the sklearn documentation for one hot encoder and it says “ Encode categorical integer ...

Author: David M. Cooke, Francesc Alted, and others. NumExpr is a fast numerical expression evaluator for NumPy. With it, expressions that operate on arrays (like '3*a+4*b') are accelerated and use ...

There is a phenomenon in the Python programming language that affects the efficiency of data representation and memory. I call it the "invisible line." This invisible line might seem innocuous at ...

But in many cases, it doesn’t have to be an either/or proposition. Properly optimized, Python applications can run with surprising speed—perhaps not as fast as Java or C, but fast enough for web ...

NumPy is known for being fast, but could it go even faster? Here’s how to use Cython to accelerate array iterations in NumPy. NumPy gives Python users a wickedly fast library for working with data in ...