{"id":43237626,"url":"https://github.com/skrub-data/skrub-tutorials","last_synced_at":"2026-02-01T11:11:10.254Z","repository":{"id":322654592,"uuid":"1090284550","full_name":"skrub-data/skrub-tutorials","owner":"skrub-data","description":"This repository contains material used for tutorials, courses and MOOCs on skrub","archived":false,"fork":false,"pushed_at":"2026-01-14T15:55:43.000Z","size":31489,"stargazers_count":3,"open_issues_count":2,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2026-01-14T19:08:45.336Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"https://skrub-data.org/skrub-tutorials/","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"bsd-3-clause","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/skrub-data.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2025-11-05T13:14:49.000Z","updated_at":"2026-01-14T15:54:28.000Z","dependencies_parsed_at":null,"dependency_job_id":"05a74c6b-e1de-41c5-bbe1-a55757744f07","html_url":"https://github.com/skrub-data/skrub-tutorials","commit_stats":null,"previous_names":["skrub-data/skrub-tutorials"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/skrub-data/skrub-tutorials","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/skrub-data%2Fskrub-tutorials","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/skrub-data%2Fskrub-tutorials/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/skrub-data%2Fskrub-tutorials/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/skrub-data%2Fskrub-tutorials/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/skrub-data","download_url":"https://codeload.github.com/skrub-data/skrub-tutorials/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/skrub-data%2Fskrub-tutorials/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28977317,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-01T09:57:52.632Z","status":"ssl_error","status_checked_at":"2026-02-01T09:57:49.143Z","response_time":56,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2026-02-01T11:11:09.618Z","updated_at":"2026-02-01T11:11:10.245Z","avatar_url":"https://github.com/skrub-data.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Introduction to the course\nThis is the website for the \n[Inria Academy course](https://www.inria-academy.fr/formation/skrub-like-a-pro-clean-prepare-and-transform-your-data-faster/)\non the [skrub package](https://skrub-data.org/stable/): it contains all the material\nused for the course, including the datasets and exercises used during the session. \n\n## Beta warning\nIf you are reading this, then you will be attending the **Beta version** of this \ncourse. As a **Beta version**, this is not the final version of the course and \nit will be tweaked according to the feedback provided after the session. \n\nBoth the presentation and the content of the book are liable to be changed based\non feedback. \n\n## Structure of the course\nThe course covers the main features of skrub, from data exploration to pipeline \nconstruction, with the notable exclusion of the Data Ops.\n\nEach chapter includes a section that describes how a specific feature may assist\nin building a machine learning pipeline, along with practical code examples. \n\nSome chapters include exercises for participants to work with the explained features.\nThese exercises are made available in `content/exercises`, as well as at the end\nof the respective lesson in `content/notebooks`. \n\nThe content of the book is split in sections, and each section includes a \"final \nquiz\" that covers the subjects covered up to that point. \n\n# Prepration and setup\nFirst of all, clone the [GitHub repo](https://github.com/skrub-data/skrub-tutorials/tree/main) \nof this book to have access to the exercises. In a future version, Jupyterlite \nwill be made available. \n\n## Setting up a local environment\n\n### Finding the material\nFollowing any of the following commands should let you open a Jupyter lab or \nnotebook instance in the root of the folder. Then, you will find all the course \nmaterial as notebooks in `content/notebooks`, and only the exercises in \n`content/exercises`. \n\nAll the datasets are made available to the notebooks by cloning the repo. \n\n### Using pixi\nThe easiest way to set up the environment is by installing and\nusing [pixi](https://pixi.sh/latest/installation/). Follow the platform-specific \ninstructions in the link to install pixi, then open a terminal window. \n\nRun \n```sh\npixi install\n```\nto create the environment, followed by \n\n```sh\npixi run lab\n``` \nto start a Jupyter lab instance. \n\n### Using `pip`\nCreate the and activate the environment:\n\n```sh\npython -m venv skrub-tutorial\nsource skrub-tutorial/bin/activate\n```\n\nInstall the required dependencies using the `requirements.txt` file:\n```sh\npip install -r requirements.txt\n```\n\nStart the Jupyter lab instance: \n```sh\njupyter lab\n```\n\n### Using conda\nAn `environment.yaml` file is provided to create a conda environment. \n\nCreate and activate the environment with\n\n```sh\nconda env create -f environment.yaml\nconda activate skrub-tutorial\n```\n\nThen, start a jupyter lab instance:\n\n```sh\njupyter lab\n```\n\n### Using `uv`\nCreate the environment using `pyproject.toml` as the requirement file. \n\n```sh\nuv venv \nuv pip install -r pyproject.toml\n```\n\nActivate the environment that was created in the folder. \n```sh\nsource .venv/bin/activate\n```\n\nStart the Jupyter lab instance: \n```sh\njupyter lab \n```","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fskrub-data%2Fskrub-tutorials","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fskrub-data%2Fskrub-tutorials","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fskrub-data%2Fskrub-tutorials/lists"}