$devvkit learn --librarie numpy-guide

NumPy Guide

[python][numerical][arrays]

Python

Install

pip install numpy

Core: ndarray: a homogeneous N-dimensional array object for fast numerical operations.

Vectorized operations run in C, 10-100x faster than Python loops.

Foundation for pandas, SciPy, scikit-learn, and TensorFlow.

Array Creation

Create array· From list.

import numpy as np
arr = np.array([1, 2, 3])

Arange· Range of values.

np.arange(0, 10, 2)  # [0, 2, 4, 6, 8]

Zeros/ones· Initialized arrays.

np.zeros((3, 4))
np.ones((2, 3))
np.eye(3)

Linspace· Evenly spaced.

np.linspace(0, 1, 5)  # [0, 0.25, 0.5, 0.75, 1]

Broadcasting· Shape-agnostic ops.

arr + 10
arr * 2
arr + np.array([10, 20, 30])

Boolean masking· Filter with mask.

arr[arr > 3]
np.where(arr > 3, 'high', 'low')

Stats· Sum, mean, std.

arr.sum()
arr.mean()
arr.std()
arr.max()
arr.min()

Dot product· Matrix multiplication.

np.dot(a, b)
a @ b  # Python 3.5+

Reshape· Change dimensions.

arr.reshape(2, 3)
arr.flatten()
arr.T  # transpose

Random· Random numbers.

np.random.rand(3, 3)
np.random.randint(0, 10, size=5)
np.random.normal(0, 1, 100)