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 ...

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.

Learn the NumPy trick for generating synthetic data that actually behaves like real data.

Web apps, web crawling, database access, GUI creation, parsing, image processing, and lots more—these handy tools have you covered Want a good reason for the smashing success of the Python programming ...