Exploratory Data Analysis with R
by Roger D. Peng
Publisher: Leanpub 2016
Number of pages: 208
This book teaches you to use R to effectively visualize and explore complex datasets. Exploratory data analysis is a key part of the data science process because it allows you to sharpen your question and refine your modeling strategies.
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by Patrick Burns - Burns Statistics
If you don't know of 'The R Inferno', this revised edition is a book-length (intermediate level) explanation of a few trouble spots when using the R language. If you are using R and you think you're in hell, this is a map for you.
by Hadley Wickham
The book is designed primarily for R users who want to improve their programming skills and understanding of the language. It should also be useful for programmers coming to R from other languages, as it explains some of R's quirks...
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Learn R programming for data analysis in a single day. The book aims to teach data analysis using R within a day to anyone who already knows some programming in any other language. The book has sample code which can be downloaded as a zip file.
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Comprehensive introduction to R, a software package for statistical computing and graphics. R supports a wide range of statistical techniques, and is easily extensible via user-defined functions, or using modules written in C, C++ or Fortran.