Ich habe mit repairData mein erstes R Paket auf CRAN veröffentlicht! Der Artikel beschreibt die Herkunft der Datensätze und die Ziele, die ich mit der Publikation verbinde.
Kategorie: Material
Books for free: Links to R related eBooks, PDFs, and other book-like material on the web.
Link collection from the Book ordered by chapters.
Link collection from the Book ordered by chapters.
A collection of sheets that contain a summary of the most important commands for a special R tool or R package.
The book „Efficient R Programming: A Practical Guide to Smarter Programming“ by Colin Gillespie & Robing Lovelace is a collection of very important resources. It is not only helpful for the advanced data scientist but also the intermediate and even R beginner can benefit a great deal from the book. It covers important R related everyday subjects and activities. Each self-contained chapter starts with 5 top five tips and discusses practical issues. The book is rich in internet references, which I have collected and presented in 10 link lists, divided by the book chapters.
Books for free: Links to R related eBooks, PDFs, and other book-like material on the web.
Books to buy: Links to web pages referring to R related books.
This form is for collecting links relating to R, a free software environment for statistical computing and graphics. For other links go to this page.
Books to buy: Links to web pages referring to R related books.
A link collection on scientific methods, processes, and systems to extract knowledge or insights from data
Books for free: Links to R related eBooks, PDFs, and other book-like material on the web.
Educational material for learning R (tutorials, web pages, videos, MOOCs, guided tours etc.)
Answers to R related questions, problem-related references on websites (e.g. Stack Overflow etc.)
Link to R related helpful material, like packages documentation, cheatsheets, style guides, …
Kickstarting R: links to help resources, especially for beginners
Links that do not fit into my other categories.
Open Data! Links to data repositories including GitHub, websites with data for downloading etc.
Links to statistics books and other material related with R and/or data analysis.
Links to R software, packages, APIs, and other tools.