An introduction to the grammar of graphics, how to use the grammar to build graphs, and how ggplot2 implements the grammar in R. Some of the code details may be out of date. An explanation of R for advanced users. The book explains R as a programming language, covering topics such as S3 and S4 methods, scoping rules, performance and much more.
Turn your R code into packages that others can easily download and use. An introduction to programming in R. The book uses three hands-on projects to teach every aspect of R programming, from loading data to writing fast, vectorized functions.
A cookbook of techniques for creating effective graphics with ggplot2 and base R. The book includes dozens of exercises distributed across most chapters. The Data Science Design Manual. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data.
The Data Science Design Manual OpenIntro Statistics. OpenIntro Statistics offers a traditional introduction to statistics at the college level. This textbook is widely used at the college level and offers an exceptional and accessible introduction for students from community colleges to the Ivy League. The textbook has been thoroughly vetted with an estimated 20, students using it annually. No knowledge of R is assumed. Through a series of worked examples, this accessible primer then demonstrates how to create plots piece by piece, beginning with summaries of single variables and moving on to more complex graphics.
Learn how to produce and refine plots. The worked examples are a real godsend. Next page: Page 2 — R Graphics Cookbook and more books. This site uses Akismet to reduce spam. Learn how your comment data is processed. Skip to content The R language is the de facto standard among statisticians for the development of statistical software, and is widely used for statistical software development and data analysis.
So anyone can repeat your work whatever platform they run. A huge set of high quality packages for statistical modelling, machine learning, visualisation, and importing and manipulating data. Cutting edge tools. A suite of operators for calculations on arrays, in particular matrices. Deep-seated language support for data analysis. This includes features likes missing values, data frames, and subsetting.
Powerful tools for communicating your results. Produce publication-quality graphs, including mathematical symbols.
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