This repository contains a Jupyter Notebook demonstrating various operations on arrays using Python's built-in array module. It includes examples of creating, accessing, modifying, and iterating over ...

Create an rng object with np.random.default_rng(), you can seed it for reproducible results. You can draw samples from probability distributions, including from the binomial and normal distributions.

Tired of out-of-memory errors derailing your data analysis? There's a better way to handle huge arrays in Python.