{"id":19769568,"url":"https://github.com/tjmahr/madr_pipelines","last_synced_at":"2025-04-30T17:31:24.729Z","repository":{"id":29007237,"uuid":"32534255","full_name":"tjmahr/MadR_Pipelines","owner":"tjmahr","description":"Slides and materials for my talk to the Madison R Users Group","archived":false,"fork":false,"pushed_at":"2015-06-17T20:26:06.000Z","size":1323,"stargazers_count":31,"open_issues_count":0,"forks_count":9,"subscribers_count":2,"default_branch":"master","last_synced_at":"2023-06-28T12:20:40.384Z","etag":null,"topics":["data-science","dplyr","magrittr","presentation","r"],"latest_commit_sha":null,"homepage":"","language":"HTML","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/tjmahr.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}},"created_at":"2015-03-19T16:47:37.000Z","updated_at":"2023-02-09T15:57:24.000Z","dependencies_parsed_at":"2022-09-04T14:12:34.697Z","dependency_job_id":null,"html_url":"https://github.com/tjmahr/MadR_Pipelines","commit_stats":null,"previous_names":[],"tags_count":null,"template":null,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tjmahr%2FMadR_Pipelines","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tjmahr%2FMadR_Pipelines/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tjmahr%2FMadR_Pipelines/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tjmahr%2FMadR_Pipelines/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/tjmahr","download_url":"https://codeload.github.com/tjmahr/MadR_Pipelines/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":224219737,"owners_count":17275477,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","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","dplyr","magrittr","presentation","r"],"created_at":"2024-11-12T04:43:50.792Z","updated_at":"2024-11-12T04:43:51.397Z","avatar_url":"https://github.com/tjmahr.png","language":"HTML","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Let the Data Flow: Pipelines in R with dplyr and magrittr\n\n## Abstract \n\n\u003e Pipelines were the best thing to happen in R in 2014. They let us transform \nmessy, inside-out code like `sort(unique(round(xs, 2)))` into a clear chain of \ntransformations like `xs %\u003e% round(2) %\u003e% unique %\u003e% sort`. In this talk I lead \na tutorial on how to use pipelines for data-cleaning, transformation and \npresentation with the packages `magrittr` and `dplyr`. For beginners, I also \nreview some of the essential R functions to make the most of pipelines.\n\u003e\n\u003e Tristan is a PhD student in Communication Sciences and Disorders. He uses in \nR in the [Learning To Talk lab](http://learningtotalk.org) to model \neye-tracking and speech perception data. [@tjmahr](https://twitter.com/tjmahr), \n[github.com/tjmahr](https://github.com/tjmahr). \n\n\n\n## Slides\n\nI prepared three sets of slides:\n\n* [Pipelines in R](http://rpubs.com/tjmahr/pipelines_2015)\n* [dplyr: verbs for manipulating data-frames](http://rpubs.com/tjmahr/dplyr_2015)\n* [Making pretty regression tables with pipes](http://rpubs.com/tjmahr/prettytables_2015)\n\n\n## Resources\n\n* [magrittr vignette](http://cran.r-project.org/web/packages/magrittr/vignettes/magrittr.html)\n* [RStudio Data-Wrangling Cheatsheet](http://www.rstudio.com/wp-content/uploads/2015/02/data-wrangling-cheatsheet.pdf)\n* [Core R vocabulary](http://adv-r.had.co.nz/Vocabulary.html)\n* [Awesome R](https://github.com/qinwf/awesome-R)\n* [Pipelines for Data Analysis](https://www.youtube.com/watch?v=40tyOFMZUSM) (dpylr/magrittr talk by Hadley Wickham)\n* [Best Practices for Scientific Computing](http://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1001745)\n* [Data Science on the Command Line](http://datascienceatthecommandline.com/)\n* [Unix Commands for Data Science](http://www.gregreda.com/2013/07/15/unix-commands-for-data-science/)\n \n### Packages\n\n* [magrittr](https://github.com/smbache/magrittr) for pipelines\n* [dplyr](https://github.com/hadley/dplyr) for data-frame functions\n* [broom](http://cran.r-project.org/web/packages/broom/index.html)\n* [stringr](http://cran.r-project.org/web/packages/stringr/index.html) for \n  string manipulation functions\n* [pipeR](https://github.com/renkun-ken/pipeR) an alternative pipeline package\n  (that I haven't tried yet).\n\n## License\n\nObviously, the GPL-2 license applies only to the code and words I wrote, which \nare in the `.Rpres` and `.md` files and are reproduced with markup in the \n`.html` files.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftjmahr%2Fmadr_pipelines","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftjmahr%2Fmadr_pipelines","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftjmahr%2Fmadr_pipelines/lists"}