{"id":20356555,"url":"https://github.com/madhurimarawat/r-for-datascience","last_synced_at":"2026-04-26T08:37:44.504Z","repository":{"id":186570588,"uuid":"675380333","full_name":"madhurimarawat/R-for-Datascience","owner":"madhurimarawat","description":"This repository contains Programs in the R programming language.","archived":false,"fork":false,"pushed_at":"2023-09-28T16:56:42.000Z","size":396,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-11-07T13:02:49.440Z","etag":null,"topics":["basic-programs","conditional-statements","csv-files","data-types","data-visualization","dataframe","dot-functions","functions","ggplot2","iris-dataset","lists","non-numeric-values","pattern-printing","r","user-input","vectors"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","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/madhurimarawat.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}},"created_at":"2023-08-06T18:10:52.000Z","updated_at":"2023-09-28T16:56:47.000Z","dependencies_parsed_at":null,"dependency_job_id":"7be9c81f-7ec1-4f2f-9d11-a7ad156b27db","html_url":"https://github.com/madhurimarawat/R-for-Datascience","commit_stats":null,"previous_names":["madhurimarawat/r-for-datascience"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/madhurimarawat/R-for-Datascience","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/madhurimarawat%2FR-for-Datascience","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/madhurimarawat%2FR-for-Datascience/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/madhurimarawat%2FR-for-Datascience/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/madhurimarawat%2FR-for-Datascience/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/madhurimarawat","download_url":"https://codeload.github.com/madhurimarawat/R-for-Datascience/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/madhurimarawat%2FR-for-Datascience/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32291207,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-26T08:29:33.829Z","status":"ssl_error","status_checked_at":"2026-04-26T08:29:18.366Z","response_time":129,"last_error":"SSL_read: 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":["basic-programs","conditional-statements","csv-files","data-types","data-visualization","dataframe","dot-functions","functions","ggplot2","iris-dataset","lists","non-numeric-values","pattern-printing","r","user-input","vectors"],"created_at":"2024-11-14T23:17:01.965Z","updated_at":"2026-04-26T08:37:44.499Z","avatar_url":"https://github.com/madhurimarawat.png","language":"Jupyter Notebook","readme":"# R-for-Datascience\nThis repository contains Programs in the R Programming Language.\u003cbr\u003e\u003cbr\u003e\n\u003cimg src=\"https://github.com/madhurimarawat/R-for-Datascience/assets/105432776/700e39ba-791c-4a2b-9d6b-e74bdbd3d1f7\"\u003e\n\n# About R Programming\n\n--\u003e R is an open-source programming language that is widely used as a statistical software and data analysis tool.\u003cbr\u003e\u003cbr\u003e\n--\u003e R generally comes with the Command-line interface.\u003cbr\u003e\u003cbr\u003e\n--\u003e R is available across widely used platforms like Windows, Linux, and macOS.\u003cbr\u003e\u003cbr\u003e\n--\u003e R also provides rich Library support.\u003cbr\u003e\n\n---\n\n# Modes of Executions\nRprogramming language can be executed in the following two modes:\n\u003ch2\u003e1. Interactive mode\u003c/h2\u003e\n\u003ch3\u003ea) R Studio\u003c/h3\u003e\nR can also be run on the R Studio IDLE. It is an acronym of \"Integrated DeveLopment Environment\".\u003cbr\u003e\n\u003ch3\u003eb) Google Colab\u003c/h3\u003e\nColaboratory, or “Colab” for short, is a product from Google Research which allows anybody to write and execute r code in Jupyter notebook through the browser.\u003cbr\u003e\n\u003ch2\u003e2. Script mode\u003c/h2\u003e\nR programs are written in editors and saved as the file with the .r extension which can be executed further. \u003cbr\u003e\n\n---\n\n# Basic Datatypes\n \u003cimg src=\"https://cdn.educba.com/academy/wp-content/uploads/2019/11/r-data-types.png\" height=400 width=680 title=\"Datatypes-of-R-programming\" alt=\"Datatypes-of-R-programming\"\u003e\n\nR data types are the essential features that accept and store various data types.\n\nSome of the most common data types in R are:\n\u003col\u003e\n\u003cli\u003eNumeric: Decimal numbers like 10.5, 55, 787.\u003c/li\u003e  \u003cbr\u003e\n\u003cli\u003eInteger: Whole numbers like 1L, 55L, and 100L (the letter “L” declares this as an integer).\u003c/li\u003e \u003cbr\u003e\n\u003cli\u003eCharacter: Strings of text like “hello”, “R”, and “data”.\u003c/li\u003e \u003cbr\u003e\n\u003cli\u003eLogical: Boolean values like TRUE or FALSE.\u003c/li\u003e \u003cbr\u003e\n\u003cli\u003eFactor: Categorical variables like “red”, “green”, and “blue”.\u003c/li\u003e \u003cbr\u003e\n\u003cli\u003eVector: A collection of elements of the same data type like c(1,2,3) or c(“a”,“b”,“c”).\u003c/li\u003e\n\u003cbr\u003e \u003cp\u003e Vectors are of two types\u003c/p\u003e\n \u003col\u003e\n  \u003cli\u003eAtomic Vectors-Sequence of same data type that share the same data type. \u003c/li\u003e\n  \u003cli\u003eList- Lists are a \"recursive\" type (of vector), i.e list can hold non-homogeneous data type.\u003c/li\u003e\n \u003c/ol\u003e\n \u003cbr\u003e\n\u003cli\u003eMatrix: A two-dimensional array of elements of the same data type like matrix(1:9,nrow=3).\u003c/li\u003e  \u003cbr\u003e\n\u003cli\u003eData frame: A table-like structure with rows and columns that can have different data types like data.frame(name=c(“Alice”,“Bob”),age=c(25,30)).\u003c/li\u003e  \u003cbr\u003e\n\u003cli\u003eList: It is a collection of elements that can have different data types like list(name=“Alice”,age=25,scores=c(90,80,70)).\u003c/li\u003e  \u003cbr\u003e\n \u003cli\u003eArray: It is a list or vector with two or more dimensions. An array is like a stacked matrix; a matrix is a two-dimensional array.\u003c/li\u003e\n\u003c/ol\u003e\n\n ---\n\n# Features of R\n\u003cimg src=\"https://github.com/madhurimarawat/R-for-Datascience/assets/105432776/f9942f22-3f51-42fc-ad5a-5be86e60e4f4\" height=400 width=680 title=\"Features-of-R-programming\" alt=\"Features-of-R-programming\"\u003e\n\n---\n# Mode of Execution Used:  \u003cimg src=\"https://logos-download.com/wp-content/uploads/2020/06/RStudio_Logo.png\" title=\"R Studio\" alt=\"R Studio\" width=\"40\" height=\"40\"\u003e\n\u003ch2\u003eR\u003c/h2\u003e\n--\u003e Visit the official website: \u003ca href=\"https://www.r-project.org/\"\u003e \u003cimg src=\"https://github.com/devicons/devicon/blob/master/icons/r/r-original.svg\" title=\"R Language\" alt=\"R\" width=\"40\" height=\"40\"\u003e \u003c/a\u003e \u003cbr\u003e \u003cbr\u003e\n--\u003e Download according to the platform that will be used like Linux, Macos or Windows.\u003cbr\u003e\u003cbr\u003e\n--\u003e Follow the setup wizard.\u003cbr\u003e\n\u003ch2\u003eR Studio\u003c/h2\u003e\n--\u003e Visit the official website: \u003ca href=\"https://www.rstudio.com/categories/rstudio-ide/\"\u003e \u003cimg src=\"https://logos-download.com/wp-content/uploads/2020/06/RStudio_Logo.png\" title=\"R Studio\" alt=\"R Studio\" width=\"40\" height=\"40\"\u003e\u003c/a\u003e \u003cbr\u003e \u003cbr\u003e\n--\u003e Download according to the platform that will be used like Linux, Macos or Windows.\u003cbr\u003e\u003cbr\u003e\n--\u003e Follow the setup wizard.\u003cbr\u003e\u003cbr\u003e\n--\u003e Create a new file with the extention of .r and then this file can be executed in the console.\n\n---\n # Dataset Used\n\n \u003ch2\u003eIris Dataset\u003c/h2\u003e\n--\u003e Iris has 4 numerical features and a tri class target variable.\u003cbr\u003e\u003cbr\u003e\n--\u003e This dataset can be used for classification as well as clustering.\u003cbr\u003e\u003cbr\u003e\n--\u003e In this dataset, there are 4 features sepal length, sepal width, petal length and petal width and the target variable has 3 classes namely ‘setosa’, ‘versicolor’, and ‘virginica’.\u003cbr\u003e\u003cbr\u003e\n--\u003e Dataset is already cleaned,no preprocessing required.\u003cbr\u003e\u003cbr\u003e\n--\u003e This dataset is simply used for understanding CSV features and data Visualization.\u003cbr\u003e\n\n\u003ch2\u003eAutomobile Dataset\u003c/h2\u003e\n--\u003e Dataset is taken from: \u003ca href=\"https://gist.github.com/lauvshree/20ee07bfaa6d97364006fc2320092526\"\u003e🔗\u003cimg src=\"https://github.com/devicons/devicon/blob/master/icons/github/github-original-wordmark.svg\" height =40 width=40 title=\"Automobile Dataset\" alt=\"Automobile Dataset\"\u003e \u003c/a\u003e\u003cbr\u003e\u003cbr\u003e\n--\u003e This contains data about various automobile in Comma Separated Value (CSV) format.\u003cbr\u003e\u003cbr\u003e\n--\u003e CSV file contains the details of automobile-mileage,length,body-style among other attributes.\u003cbr\u003e\u003cbr\u003e\n--\u003e It contains the following dimensions-[60 rows X 6 columns].\u003cbr\u003e\u003cbr\u003e\n--\u003e The csv file is already preprocessed ,thus their is no need for data cleaning.\u003cbr\u003e\n\n\u003ch2\u003eNBA Players Dataset\u003c/h2\u003e\n--\u003e Dataset is taken from: \u003ca href=\"https://gist.github.com/ganeshbabuNN/80b55569fde8eb6a81518d4c8921c7a6\" \u003e🔗\u003cimg src=\"https://github.com/devicons/devicon/blob/master/icons/github/github-original-wordmark.svg\" height =40 width=40 title=\"NBA Dataset\" alt=\"NBA Dataset\"\u003e \u003c/a\u003e\u003cbr\u003e\u003cbr\u003e\n--\u003e This contains data about various NBA Players in Comma Separated Value (CSV) format.\u003cbr\u003e\u003cbr\u003e\n--\u003e CSV file contains the details of players-height,weight,team,position among other attributes.\u003cbr\u003e\u003cbr\u003e\n--\u003e It contains the following dimensions-[457 rows X 9 columns].\u003cbr\u003e\u003cbr\u003e\n--\u003e The csv file is already preprocessed ,thus their is no need for data cleaning.\u003cbr\u003e\n\n---\n# Libraries of R\n\nTo install R library this command is used-\u003cbr\u003e\n```\ninstall.packages(library_name)\n```\n\u003cimg src=\"https://github.com/madhurimarawat/R-for-Datascience/assets/105432776/3ed5f9fc-b8ad-4c17-a730-f4ef59e5a303\" height=400 width=680 title=\"Libraries-of-R-programming\" alt=\"Libraries-of-R-programming\"\u003e\n\n---\n\n## Thanks for Visiting 😄\n\nDrop a 🌟 if you find this repository useful.\u003cbr\u003e\u003cbr\u003e\nIf you have any doubts or suggestions, feel free to reach me.\u003cbr\u003e\u003cbr\u003e\n📫 How to reach me:  \u0026nbsp; [![Linkedin Badge](https://img.shields.io/badge/-madhurima-blue?style=flat\u0026logo=Linkedin\u0026logoColor=white)](https://www.linkedin.com/in/madhurima-rawat/) \u0026nbsp; \u0026nbsp;\n\u003ca href =\"mailto:rawatmadhurima4@gmail.com\"\u003e\u003cimg src=\"https://github.com/madhurimarawat/Machine-Learning-Using-Python/assets/105432776/b6a0873a-e961-42c0-8fbf-ab65828c961a\" height=35 width=30 title=\"Mail Illustration\" alt=\"Mail Illustration📫\" \u003e \u003c/a\u003e\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmadhurimarawat%2Fr-for-datascience","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmadhurimarawat%2Fr-for-datascience","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmadhurimarawat%2Fr-for-datascience/lists"}