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rougier/numpy-100

A set of 100 NumPy exercises with solutions, aimed at learning and quick reference for Python array computing.

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What is it?

This repository collects 100 exercises for NumPy, the Python library for numerical array computing. The problems are drawn from the NumPy mailing list, Stack Overflow and the NumPy documentation, with some written by the author to reach the total of 100.

The exercises serve two purposes: a quick reference for both newcomers and experienced users, and a ready-made problem set for instructors. The content is maintained in a single source file and generated into Markdown and Jupyter notebook versions, and the notebook can be run online through Binder without local setup. A Julia variant of the collection also exists.

Key features

  • 01Covers 100 NumPy problems ranging across array creation, indexing and arithmetic.
  • 02Provides solutions alongside each exercise.
  • 03Available as both a Markdown file and a Jupyter notebook.
  • 04Can be run online via Binder without local installation.
  • 05Content is generated from a single source file to keep formats in sync.

Use cases

  • Practicing NumPy after learning basic Python.
  • Preparing exercises or assignments for a numerical computing course.
  • Looking up common NumPy idioms as a quick reference.

Quick start

  1. 1

    Open the exercise notebook on Binder to run it in your browser

In collections

Data science courses & tools

Topics

#numpy#python#exercises#data-science#jupyter#learning#binder#notebook

FAQ

What is numpy-100?
A set of 100 NumPy exercises with solutions, aimed at learning and quick reference for Python array computing. This repository collects 100 exercises for NumPy, the Python library for numerical array computing. The problems are drawn from the NumPy mailing list, Stack Overflow and the NumPy documentation, with some written by the author to reach the total of 100.
Is numpy-100 free to use? What license does it have?
numpy-100 is open source under the MIT license. Check the license terms before using it in commercial products.
Is numpy-100 still maintained?
Actively maintained. The last commit to numpy-100 was on Oct 23, 2026.
What can I use numpy-100 for?
Practicing NumPy after learning basic Python. Preparing exercises or assignments for a numerical computing course. Looking up common NumPy idioms as a quick reference.
How do I install numpy-100?
Open the exercise notebook on Binder to run it in your browser
Where can I get numpy-100?
The source code and installation instructions are on GitHub: https://github.com/rougier/numpy-100

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