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

If you want to analyze data in Python, you'll want to become familiar with pandas, as it makes data analysis so much easier. The DataFrame is the primary data format you'll interact with. Here's how ...

Python is convenient and flexible, yet notably slower than other languages for raw computational speed. The Python ecosystem has compensated with tools that make crunching numbers at scale in Python ...

NumPy (Numerical Python) is an open-source library for the Python programming language. It is used for scientific computing and working with arrays. Apart from its multidimensional array object, it ...

[Zoltán] sends in his very interesting implementation of a NumPy-like library for micropython called ulab. He had a project in MicroPython that needed a very fast FFT on a micro controller, and was ...

In December 2019 my InfoWorld colleague Sharon Machlis wrote an article called “How to merge data in R using R merge, dplyr, or data.table.” Sharon is a whiz at R programming, and analytics in general ...

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 ...