{"id":43965378,"url":"https://github.com/mnr/r-for-data-science-lunchbreak-lessons","last_synced_at":"2026-02-07T06:30:47.394Z","repository":{"id":51061111,"uuid":"88918201","full_name":"mnr/R-for-Data-Science-Lunchbreak-Lessons","owner":"mnr","description":"Source files for the LinkedIn Learning Course","archived":false,"fork":false,"pushed_at":"2024-03-03T07:33:55.000Z","size":17523,"stargazers_count":90,"open_issues_count":0,"forks_count":54,"subscribers_count":19,"default_branch":"master","last_synced_at":"2025-09-04T20:31:53.522Z","etag":null,"topics":["data-science","linkedin-learning","mark-niemann-ross","r","rlang","rstats","tutorials"],"latest_commit_sha":null,"homepage":"https://linkedin-learning.pxf.io/r_lunchbreak","language":"HTML","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/mnr.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":".github/FUNDING.yml","license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":"CITATION.cff","codeowners":null,"security":null,"support":"support text files/asciiDailyTemp.txt","governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null},"funding":{"github":["mnr"],"patreon":null,"open_collective":null,"ko_fi":null,"tidelift":null,"community_bridge":null,"liberapay":null,"issuehunt":null,"otechie":null,"lfx_crowdfunding":null,"polar":null,"custom":null}},"created_at":"2017-04-20T23:09:10.000Z","updated_at":"2025-03-22T22:11:06.000Z","dependencies_parsed_at":"2024-03-03T08:38:19.766Z","dependency_job_id":null,"html_url":"https://github.com/mnr/R-for-Data-Science-Lunchbreak-Lessons","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/mnr/R-for-Data-Science-Lunchbreak-Lessons","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mnr%2FR-for-Data-Science-Lunchbreak-Lessons","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mnr%2FR-for-Data-Science-Lunchbreak-Lessons/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mnr%2FR-for-Data-Science-Lunchbreak-Lessons/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mnr%2FR-for-Data-Science-Lunchbreak-Lessons/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/mnr","download_url":"https://codeload.github.com/mnr/R-for-Data-Science-Lunchbreak-Lessons/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mnr%2FR-for-Data-Science-Lunchbreak-Lessons/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29188226,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-07T05:07:31.176Z","status":"ssl_error","status_checked_at":"2026-02-07T05:06:15.227Z","response_time":63,"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":["data-science","linkedin-learning","mark-niemann-ross","r","rlang","rstats","tutorials"],"created_at":"2026-02-07T06:30:46.842Z","updated_at":"2026-02-07T06:30:47.388Z","avatar_url":"https://github.com/mnr.png","language":"HTML","funding_links":["https://github.com/sponsors/mnr"],"categories":[],"sub_categories":[],"readme":"# R Language Mini Tutorials\n[Source files for the LinkedIn Learning Course](http://niemannross.com/link/rlunchlessons)\n\nProgramming is learned in small bits. You build on basic concepts. You transfer the knowledge you already have to the next language. Lunch Break Lessons teaches R—one of the most popular programming languages for data analysis and reporting—in short lessons that expand on what existing programmers already know.\n\nThe five minutes you spend each week will provide you with a building block you can use in the next two hours at work. Review language basics, discover methods to improve existing R code, explore new and interesting features, and learn about useful development tools and libraries that will make your time programming with R that much more productive.\n\nCopyright Mark Niemann-Ross, 2017 - [join the discussion](https://groups.google.com/d/forum/r-for-data-science-lunchbreak-lessons) - [My LinkedIn Profile](https://www.linkedin.com/in/markniemannross/) - [My Github account](https://github.com/mnr) - [More of my courses at LinkedIn Learning](https://linkedin-learning.pxf.io/mnr) - [niemannross.com](http://www.niemannross.com)\n\n# Index to topics covered in my LinkedIn Learning R courses\n\n[apply](https://linkedin-learning.pxf.io/apply)  \n[apropos](https://linkedin-learning.pxf.io/apply)  \n[array](https://linkedin-learning.pxf.io/rweekly_array)  \n[barplot()](https://linkedin-learning.pxf.io/rweekly_factor)  \n[cbind](https://linkedin-learning.pxf.io/rweekly_cbind)  \n[change\nvariable](https://linkedin-learning.pxf.io/data.frame_read_update)  \n[character](https://linkedin-learning.pxf.io/rweekly_atomics)  \n[complex](https://linkedin-learning.pxf.io/rweekly_atomics)  \n[create\nvariable](https://linkedin-learning.pxf.io/data.frame_read_update)  \n[data()](https://linkedin-learning.pxf.io/rwkly_dataSets)  \n[data.frame](https://linkedin-learning.pxf.io/rweekly_dataframe)  \n[delete\nvariable](https://linkedin-learning.pxf.io/data.frame_read_update)  \n[dimnames](https://linkedin-learning.pxf.io/rweekly_array)  \n[factor](https://linkedin-learning.pxf.io/rweekly_factor)  \n[integer](https://linkedin-learning.pxf.io/rweekly_atomics)  \n[lapply](https://linkedin-learning.pxf.io/apply)  \n[levels()](https://linkedin-learning.pxf.io/rweekly_factor)  \n[list](https://linkedin-learning.pxf.io/rweekly_lists)  \n[logical](https://linkedin-learning.pxf.io/rweekly_atomics)  \n[matrix](https://linkedin-learning.pxf.io/rweekly_matrix)  \n[merge](https://linkedin-learning.pxf.io/rweekly_sortmerge)  \n[nlevels()](https://linkedin-learning.pxf.io/rweekly_factor)  \n[order](https://linkedin-learning.pxf.io/rweekly_sortmerge)  \n[ordered()](https://linkedin-learning.pxf.io/rweekly_factor)  \n[raw](https://linkedin-learning.pxf.io/rweekly_atomics)  \n[rbind](https://linkedin-learning.pxf.io/rbind)  \n[real](https://linkedin-learning.pxf.io/rweekly_atomics)  \n[sort](https://linkedin-learning.pxf.io/rweekly_sortmerge)  \n[str()](https://linkedin-learning.pxf.io/rweekly_lists)  \n[string](https://linkedin-learning.pxf.io/rweekly_atomics)  \n[sum()](https://linkedin-learning.pxf.io/rweekly_factor)  \n[t()](https://linkedin-learning.pxf.io/rweekly_matrix)  \n[table()](https://linkedin-learning.pxf.io/rweekly_factor)  \n[vector math](https://linkedin-learning.pxf.io/rweekly_vectormath)  \n[vector subsetting](https://linkedin-learning.pxf.io/rweekly_subset)  \n[vectors](https://linkedin-learning.pxf.io/rwkly_vector)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmnr%2Fr-for-data-science-lunchbreak-lessons","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmnr%2Fr-for-data-science-lunchbreak-lessons","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmnr%2Fr-for-data-science-lunchbreak-lessons/lists"}