As the ultimate numerical layer in Python, NumPy enables one to perform array and matrix operations along with host of advanced mathematical operations including the ones that can be done on arrays.

Want to get better performance with Python? Here's how to use NumPy to toe the 'invisible line' of data and memory transfers and optimize efficiency.

Proposed new feature or change: Sort single character (S1 or U1) arrays using an underlying integer representation to improve speed. Background: With a np.array of characters (U1/S1), np.unique is ...

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 ...

NumPy or Numeric Python is a powerful library for scientific calculations. It works with ndarray (array object in NumPy) that could be single or multi- dimensional. o perform different calculations ...

This post shows you how to use arrays in Python and why this data structure is so useful. A foundational skill for data science, coding, and more!

[Austin Adee] came into some drill bits. A lot of them actually. But when thousands of assorted sizes are delivered in one disorganized box, are they actually useful? Not unless you’re drilli… ...