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Last edited by
Mar 09, 2017
: R is a free software environment for statistical computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS.
It includes a GUI interface for Windows (Mac?, Linux?), but it's quite rudimentary. You might (will probably) like
Download R for
Free & very capable environment for working with R. Seems to be a defacto standard for many.
Download R first, see above.
: You want RStudio Desktop / Open Source Edition.
These books are free to read online, but you can also purchase them in digital and paper formats:
R for Data Science
Efficient R Programming
There are several nice cheat sheets
on the RStudio website.
A data.table cheat sheet is
. Lots of great resources including presentations and videos.
Check out the data.table
Introduction to data.table
Nice and very recent presentation
THE #RDATATABLE PACKAGE + new developments in v1.10.0
Search for data.table on
Concept is that most data manipulation and cleaning can be boiled down to a set of verbs
The use of action verbs and piping with descriptive variable naming leads to very readable code output.
Intro to dplyr and vignettes
A workflow for data manipulation, tidying, processing with dplyr
PDF Cheatsheet for dplyr/tidyr
Good for putting R-based analysis tools on the internet, where people can interact through a web browser without having to know or install R
Also good for developing GUI-based tools for use from within R-Studio
Getting this shined up and ready for CRAN will involve some work, and
has a good breadth of coverage
Also lots of devtools info in the book
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