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An Introduction to R
R is an integrated suite of software facilities for data manipulation, calculation and graphical display. Among other things it has
an effective data handling and storage facility, a suite of operators for calculations on arrays, in particular matrices, a large, coherent, integrated collection of intermediate tools for data analysis, graphical facilities for data analysis and display either directly at the computer or on hard-copy, and a well developed, simple and effective programming language (called 'S') which includes conditionals, loops, user defined recursive functions and input and output facilities. (Indeed most of the system supplied functions are themselves written in the S language.)
The term "environment" is intended to characterize it as a fully planned and coherent system, rather than an incremental accretion of very specific and inflexible tools, as is frequently the case with other data analysis software.
R is very much a vehicle for newly developing methods of interactive data analysis. It has developed rapidly, and has been extended by a large collection of packages. However, most programs written in R are essentially ephemeral, written for a single piece of data analysis.
an effective data handling and storage facility, a suite of operators for calculations on arrays, in particular matrices, a large, coherent, integrated collection of intermediate tools for data analysis, graphical facilities for data analysis and display either directly at the computer or on hard-copy, and a well developed, simple and effective programming language (called 'S') which includes conditionals, loops, user defined recursive functions and input and output facilities. (Indeed most of the system supplied functions are themselves written in the S language.)
The term "environment" is intended to characterize it as a fully planned and coherent system, rather than an incremental accretion of very specific and inflexible tools, as is frequently the case with other data analysis software.
R is very much a vehicle for newly developing methods of interactive data analysis. It has developed rapidly, and has been extended by a large collection of packages. However, most programs written in R are essentially ephemeral, written for a single piece of data analysis.
106 pages, Paperback
First published May 1, 2002
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Displaying 1 - 6 of 6 reviews
August 3, 2019
Somewhere in my apartment I'm sure I've still got my ancient copy of The C Programming Language, which is still my mental template of what a language specification should look like. (Actually, the Platonic ideal was Jensen & Wirth's Pascal User Manual and Report with its wondrous syntax diagrams in Appendix D, which made very clear how to write a recursive lexical analysis/parser when it came time to write a compiler, but I used C professionally, not Pascal, so knew it much deeper back then.)
In comparison, this book is pretty lame. The structure didn't seem to have much clarity, and there were quite a few aspects that just left me clueless. I still don't know if the language has overloading, for example (some aspects of rendering a plot seem to indicate that the plus operator may be overloaded in building graphics before rendering? Not sure…)
I'm not complaining too deeply, because there's lots more out there, and this reference is free. I'm enjoying learning a new language for the first time in several decades, and 𝑹 is pretty cool (RStudio makes it pretty painless, too, although I still haven't figured out how to use the debugging facility.) I've just opened up R for Data Science: Import, Tidy, Transform, Visualize, and Model Data which has great ratings here. There's not much on Shiny, though, so I'll need to find something on that when I get to it.
In comparison, this book is pretty lame. The structure didn't seem to have much clarity, and there were quite a few aspects that just left me clueless. I still don't know if the language has overloading, for example (some aspects of rendering a plot seem to indicate that the plus operator may be overloaded in building graphics before rendering? Not sure…)
I'm not complaining too deeply, because there's lots more out there, and this reference is free. I'm enjoying learning a new language for the first time in several decades, and 𝑹 is pretty cool (RStudio makes it pretty painless, too, although I still haven't figured out how to use the debugging facility.) I've just opened up R for Data Science: Import, Tidy, Transform, Visualize, and Model Data which has great ratings here. There's not much on Shiny, though, so I'll need to find something on that when I get to it.
September 30, 2016
I got this book as I am learning R for a class. I think it will be helpful, though it appears that R is not so much on the user interface side. I will need to - most likely - attach R to something else that is more interface related to get to the place I need to get to.
Still, as far as languages goes, this really is one of the most straight forward languages I have encountered for statistical stuff. The guide does seem pretty straight forward, but then again, I am a novice, so it was perfect for me.
Still, as far as languages goes, this really is one of the most straight forward languages I have encountered for statistical stuff. The guide does seem pretty straight forward, but then again, I am a novice, so it was perfect for me.
January 20, 2020
A very succinct intro.
May 21, 2022
It is basic book on R programming but actually helps little for those who are beginners.
June 28, 2014
Very Nice introduction to R, but in the middle it's get a little confuse. Unless that this is a very great introduction book about this free and open source programming language R.
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September 13, 2018its trash
Displaying 1 - 6 of 6 reviews