Introduction to SciPy

SciPy builds on NumPy's arrays to add ready-made scientific computing tools: statistics, optimization, signal processing, and linear algebra, so you don't hand-roll these algorithms yourself.

`scipy.stats` provides distributions and statistical tests — e.g. running a t-test to compare two groups takes one function call instead of implementing the formula by hand.

SciPy is organized into subpackages by domain (`scipy.optimize`, `scipy.linalg`, `scipy.integrate`) — you import only the subpackage you need for the problem at hand.