{"id":18963735,"url":"https://github.com/tirendazacademy/r-programming-tutorial","last_synced_at":"2026-01-28T14:01:27.885Z","repository":{"id":112726925,"uuid":"362166240","full_name":"TirendazAcademy/R-Programming-Tutorial","owner":"TirendazAcademy","description":"Here are the topics talked about R tutorial in 1 YouTube video.","archived":false,"fork":false,"pushed_at":"2023-01-18T18:09:07.000Z","size":184,"stargazers_count":7,"open_issues_count":0,"forks_count":4,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-06-02T06:58:29.850Z","etag":null,"topics":["data-analysis","data-science","data-structures","data-visualization","ggplot2","logistics","preprocessing","r-programming","r-programming-projects","r-projects","regression","rstudio"],"latest_commit_sha":null,"homepage":"https://youtube.com/tirendazakademi","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/TirendazAcademy.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"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}},"created_at":"2021-04-27T15:42:59.000Z","updated_at":"2023-03-17T12:37:27.000Z","dependencies_parsed_at":null,"dependency_job_id":"b6161b21-4667-4544-a792-5400ef425898","html_url":"https://github.com/TirendazAcademy/R-Programming-Tutorial","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/TirendazAcademy/R-Programming-Tutorial","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TirendazAcademy%2FR-Programming-Tutorial","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TirendazAcademy%2FR-Programming-Tutorial/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TirendazAcademy%2FR-Programming-Tutorial/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TirendazAcademy%2FR-Programming-Tutorial/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/TirendazAcademy","download_url":"https://codeload.github.com/TirendazAcademy/R-Programming-Tutorial/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TirendazAcademy%2FR-Programming-Tutorial/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28846058,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-28T13:02:32.985Z","status":"ssl_error","status_checked_at":"2026-01-28T13:02:04.945Z","response_time":57,"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-analysis","data-science","data-structures","data-visualization","ggplot2","logistics","preprocessing","r-programming","r-programming-projects","r-projects","regression","rstudio"],"created_at":"2024-11-08T14:21:26.852Z","updated_at":"2026-01-28T14:01:27.853Z","avatar_url":"https://github.com/TirendazAcademy.png","language":null,"readme":"![](https://github.com/TirendazAcademy/R-Programming-Tutorial/blob/main/Images/R.png)\n\n[![](https://img.shields.io/badge/R-Programming-00092C?\u0026style=plastic\u0026logo=r\u0026logoColor=white)]()\n[![](https://img.shields.io/badge/GGPLOT-darkorange?\u0026style=plastic\u0026logo=ggplot\u0026logoColor=white)]()\n[![](https://img.shields.io/badge/DataScience-470D21?\u0026style=plastic\u0026logo=DataScience\u0026logoColor=white)]()\n[![](https://img.shields.io/badge/MachineLearning-darkgreen?\u0026style=plastic\u0026logo=MachineLearning\u0026logoColor=white)]()\n\n\n## Introduction to R\n\nR is a language and environment for statistical computing and graphics. R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering) and graphical techniques, and is highly extensible. One of R’s strengths is the ease with which well-designed publication-quality plots can be produced, including mathematical symbols and formulae where needed. \n\n## The R environment\n\nR is an integrated suite of software facilities for data manipulation, calculation and graphical display. It includes\n\n- an effective data handling and storage facility,\n- a suite of operators for calculations on arrays, in particular matrices,\n- a large, coherent, integrated collection of intermediate tools for data analysis,\n- graphical facilities for data analysis and display either on-screen or on hardcopy, and\n- a well-developed, simple and effective programming language which includes conditionals, loops, user-defined recursive functions and input and output facilities.\n\n## What is this repo?\n\nThis repo contains tutorials about data science with R that talked about in [1 YouTube video](https://www.youtube.com/watch?v=VUkHNM4hVvI). \n\n\u003ca href=\"http://www.youtube.com/watch?feature=player_embedded\u0026v=VUkHNM4hVvI\" target=\"_blank\"\u003e\u003cimg src=\"http://img.youtube.com/vi/VUkHNM4hVvI/0.jpg\" alt=\"IMAGE ALT TEXT HERE\" width=\"480\" height=\"360\" border=\"10\" /\u003e\u003c/a\u003e\n\nThis video covers the topics below.\n\n00:05:19 What is R? \u003cbr\u003e\n00:06:40 The advantages of R \u003cbr\u003e\n00:08:27 R setup \u003cbr\u003e\n00:09:47 R Studio setup \u003cbr\u003e\n00:10:58 How to use R Studio? \u003cbr\u003e\n00:16:17 Working space \u003cbr\u003e\n00:19:04 Packages and libraries \u003cbr\u003e\n00:23:37 Basic operators \u003cbr\u003e\n00:31:30 Vectors \u003cbr\u003e\n00:37:49 Matrix and array \u003cbr\u003e\n00:51:44 Factor \u003cbr\u003e\n00:56:43 List \u003cbr\u003e\n01:01:06 DataFrame \u003cbr\u003e\n01:06:37 Working directory \u003cbr\u003e\n01:08:27 Transform data type \u003cbr\u003e\n01:14:05 Missing value \u003cbr\u003e\n01:16:22 Reading data \u003cbr\u003e\n01:18:02 Rcmdr  \u003cbr\u003e\n01:36:56 Writing data \u003cbr\u003e\n01:42:50 Date and time \u003cbr\u003e\n01:46:53 Subset data set \u003cbr\u003e\n01:53:46 Reshape data set \u003cbr\u003e\n01:59:06 Split data set \u003cbr\u003e\n02:09:48 Dana manipulation \u003cbr\u003e\n02:17:40 Strings \u003cbr\u003e\n02:28:48 Random data \u003cbr\u003e\n02:36:12 Loop and control structures \u003cbr\u003e\n02:44:09 Loop functions \u003cbr\u003e\n02:53:01 Writing function \u003cbr\u003e\n02:59:06 Pratical plot \u003cbr\u003e\n03:10:05 Data visualization with ggplot2 \u003cbr\u003e\n03:22:27 Regression analysis \u003cbr\u003e\n03:42:51 Logistic regression analysis \u003cbr\u003e\n\n📌 If you enjoy this repo, don't forget to give me a ✨. Thanks for reading 😀\n\n🔗 Let's connect [YouTube](http://youtube.com/tirendazacademy) | [Medium](http://tirendazacademy.medium.com) | [Twitter](http://twitter.com/tirendazacademy) | [Instagram](https://www.instagram.com/tirendazacademy) 😎\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftirendazacademy%2Fr-programming-tutorial","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftirendazacademy%2Fr-programming-tutorial","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftirendazacademy%2Fr-programming-tutorial/lists"}