Skip to content

NumPy Learning Path

Get started with the fundamental package for scientific computing with Python

Getting Started with NumPy

NumPy is a foundational Python library for data science, math, and scientific computing. If you’re not coming from a scientific or math background, NumPy can seem intimidating. But, don’t worry! The tutorials below get you started with the main concepts of NumPy and really demonstrate its power.

Creating NumPy Arrays

NumPy arrays are a foundational component of NumPy. Learning how to create them programmatically is a critical skill in working with NumPy. The library provides a ton of flexibility in creating useful arrays, such as sequences of numbers or even evenly-spaced arrays.

Modifying Arrays in NumPy

Once you’ve created your arrays in NumPy, you may want to modify them. NumPy makes modifying array items easier, allowing you to map functions to each item in an array. Learn how to normalize and limit array values, map a function over each item, and so much more.

Reshaping Arrays in NumPy

Being able to reshape your arrays is an essential skill once you move into machine learning and deep learning. NumPy makes reshaping arrays incredibly simple and intuitive. The resources below guide you through the key functions you need to know.

Calculating Values with NumPy

NumPy wouldn’t be a math library without being able to calculate values. The resources below provide essential guides to working with NumPy arrays, including finding values and calculating histograms.