NumPy

When to use NumPy

Use NumPy when your data fits naturally into arrays and you need fast, predictable numerical operations.

It is a good backend for early analysis, data cleaning, simulations, and preparing data before moving to a heavier library.

Minimal example

import numpy as np

x = np.linspace(0.0, 1.0, 6)
y = x ** 2

print(y)

Working habit

Keep NumPy code explicit at first. Check array shapes often, and avoid hiding several transformations inside one long line.

print(x.shape)
print(y.shape)