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 ...

Arrays in Python give you a huge amount of flexibility for storing, organizing, and accessing data. This is crucial, not least because of Python’s popularity for use in data science. But what ...

With countless applications and a combination of approachability and power, Python is one of the most popular programming ...

How chunked arrays turned a frozen machine into a finished climate model ...

Asked on Twitter why a paper is coming out now, 15 years after NumPy's creation, Stefan van der Walt of the University of California at Berkeley's Institute for Data Science, one of the article's ...

In the spirit of continual learning and, as a follow on to my previous blog, Line Regulation Measurement Coding in Python, I thought I would continue discussing coding for measurements by providing an ...

Sitting around with "a lot of time on my hand," Dutch computer scientist Guido van Rossum decided to take on a fun little side project over Christmas break in 1989: building a new programming language ...

If you have ever tried crunching large datasets on your laptop, maybe a big CSV converted to NumPy or some scientific data from work, you have probably heard your laptop fan roar like it is about to ...

Python is incredibly popular because it's easy to learn, versatile, and has thousands of useful libraries for data science. But one thing it is not is fast. That's about to change in Python 3.11, ...