Difference between revisions of "R"

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[[Category:Programming language]]
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[[Category:Science]]
{{stub}}
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[[Category:Programming languages]]
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[[ja:R]]
 +
{{Related articles start}}
 +
{{Related|Intel C++}}
 +
{{Related articles end}}
 +
[[Wikipedia:R (programming language)|R]] is a "free software environment for statistical computing and graphics."[https://www.r-project.org/]
  
''R is a free software environment for statistical computing and graphics''  (http://www.r-project.org/).
+
== Installation ==
  
== Installing R ==
+
[[Install]] the {{Pkg|r}} package. The installation of external packages within the R environment may require {{pkg|gcc-fortran}}.
  
It is very easy to install R in Arch Linux:
+
== Usage ==
# pacman -S r
 
  
R has some dependencies in tcl and tk (required to install an R package from R). To install then:
+
To start a {{ic|R}} session, open your terminal and type this command:
  # pacman -S tcl tk
+
$ R
 +
{{Note|
 +
* Make sure to use a capital R for the command. Note that some shells use the lowercase {{ic|r}} command to repeat the last entered command. Once in your {{ic|R}} session, the prompt will change to {{ic|>}}
 +
* '''site''' refers to '''system-wide''' in R Documentation}}
 +
Run {{ic|?Startup}} to read the documentation about system file  configuration, {{ic|help()}} for the on-line help,{{ic|help.start()}} for the HTML browser interface to help, {{ic|demo()}} for some demos and {{ic|q()}} to close the session and quit.
 +
 
 +
When closing the session, you will be prompted : {{ic|Save workspace Image ?[y/n/c]}}. The ''workspace'' is your current working environment and include any user-defined objects, functions. The saved image is stored in {{ic|.RData}} format and will be automatically reloaded the next time {{ic|R}} is started. You can manually save the workspace at any time in the session with the {{ic|save.image(image.RData)}} command, save as many images as you want (eg : ''image1.RData'', ''image2.RData''). You can load image with the {{ic|load.image(image.RData)}} command at any time of your session.
 +
 
 +
{{Tip|
 +
* Tired of R's verbose startup message ? Then start {{ic|R}} with the {{ic|--quiet}} command-line option ({{ic|$ R --quiet}}). You can add {{ic|1=alias R="R --quiet"}} in one of your [[Startup files]].
 +
* Running {{ic|R}} from the command line will set R's working directory to the current directory. Opening the R GUI will set R's working directory to $HOME, unless explicitly defined in your configuration files ({{ic|.Renviron}} or {{ic|.Rprofile}}).
 +
}}
 +
 
 +
== Configuration ==
 +
 
 +
Whenever R starts, its configuration is controlled by several files.
 +
Please refer to [http://stat.ethz.ch/R-manual/R-devel/library/base/html/Startup.html Initialization at Start of an R Session] to get a detailed understanding of startup process.
 +
 
 +
=== Environment ===
 +
 
 +
R first loads '''site''' and '''user''' environment variable files.
 +
The name of the site file is controlled by the [[Environment variables]] {{ic|R_ENVIRON}} if it exists, and defaults to {{ic|/etc/R/.Renviron}}.
 +
The name of the user file is specified by {{ic|R_ENVIRON_USER}}.
 +
If that is unset, it defaults to {{ic|.Renviron}} in the curent working directory or if it exists, and {{ic|~/.Renviron}} otherwise.
 +
 
 +
Most important variables can be found on [http://stat.ethz.ch/R-manual/R-devel/library/base/html/EnvVar.html Environment Variables R Documentation].
 +
 
 +
You may disable loading environment files with {{ic|--no-environ}}
 +
 
 +
Lines in {{ic|Renviron}} file should be either comment lines starting with '''#''' or lines of the form ''name=value''.
 +
Here is a very basic {{ic|.Renviron}}:
 +
 
 +
{{hc|1=.Renviron|2=
 +
R_HOME_USER = /path/to/your/r/directory
 +
R_PROFILE_USER = ${HOME}/.config/r/.Rprofile
 +
R_LIBS_USER = /path/to/your/r/library
 +
R_HISTFILE = /path/to/your/filename.Rhistory                                            # Do not forget to append the '''.Rhistory'''
 +
MYSQL_HOME = /var/lib/mysql                 
 +
}}
 +
 
 +
 
 +
=== Profile ===
 +
 
 +
R then loads an Rprofile, which contains R code that is executed.
 +
These files are read in the following order of preference (only one file is loaded):
 +
 
 +
1. A file specified by the environment variable {{ic|R_PROFILE_USER}}.
 +
 
 +
2. {{ic|.Rprofile}} in the current working directory.
 +
 
 +
3. {{ic|$HOME/.Rprofile}}.
 +
 
 +
An {{ic|.Rprofile}} can contain arbitrary R code, though best practice suggests that one should not load packages at startup, as this hinders package upgrades and reproducibility.
 +
 
 +
{{hc|1=~/.Rprofile|2=
 +
# The .First function is called after everything else in .Rprofile is executed
 +
.First <- function() {
 +
  # Print a welcome message
 +
  message("Welcome back ", Sys.getenv("USER"),"!\n","working directory is:", getwd())
 +
}
 +
 
 +
options(digits = 12)                                          # number of digits to print. Default is 7, max is 15
 +
options(stringsAsFactors = FALSE)                            # Disable default conversion of character strings to factors
 +
options(show.signif.stars = FALSE)                            # Don't show stars indicating statistical significance in model outputs
 +
error <- quote(dump.frames("${R_HOME_USER}/testdump", TRUE)) # post-mortem debugging facilities
 +
 
 +
}}
 +
 
 +
You can add more [http://stat.ethz.ch/R-manual/R-devel/library/base/html/options.html global options] to customize your {{ic|R}} environment.
 +
See this [http://stackoverflow.com/questions/1189759/expert-r-users-whats-in-your-rprofile post] for more examples of user configurations.
 +
 
 +
=== Locale ===
 +
 
 +
Aspects of the [[Locale]] are accessed by the functions {{ic|Sys.getlocale}} and {{ic|Sys.localeconv}} within the {{ic|R}} session. Locales will be the one defined in your system.
 +
 
 +
== Managing R packages ==
 +
There are many add-on {{ic|R}} packages, which can be browsed on [http://cran.r-project.org/web/packages/available_packages_by_date.html The R Website.].
 +
 
 +
{{Note|
 +
Some R packages link to files provided by system packages. These packages will need to be reinstalled when these files are updated.}}
 +
 
 +
=== With pacman ===
 +
There are some packages available on the [[AUR]] with the prefix {{ic|r-}}. You can mix and match installing R packages with pacman and through R (below), but if you do so you should let pacman manage system packages (those that reside at {{ic|/usr/lib/R/library}}, and let R manage user-installed packages elsewhere (e.g. {{ic|~/R/library}}).
 +
 
 +
=== With R ===
 +
Packages can be installed from within {{ic|R}} using the {{ic|'''install.packages(c("pkgname"))'''}} command. You should use a local library and let pacman manage files that reside under {{ic|/usr/lib/R/library}}.
 +
 
 +
{{Note|
 +
* {{ic|'''install.packages()'''}} requires {{Pkg|tk}} to be [[install]]ed for selecting mirrors. Try installing this package if you see:
 +
 
 +
{{ic|Error: .onLoad failed in loadNamespace() for 'tcltk', details (...) }}
 +
 
 +
}}
 +
 +
Within your {{ic|R }} session, run this command to check that your user library exists and is set correctly:
 +
{{hc|> Sys.getenv("R_LIBS_USER")|
 +
[1] "/path/to/directory/R/packages"}}
 +
 
 +
Alternatively, you may install from the command line like so:
 +
 
 +
{{bc|$ R CMD INSTALL -l $R_LIBS_USER ''pkg1 pkg2 ...''}}
  
Some external packages may require to be compile in Fortran as well, so installing gcc-fortran can be a good idea:
+
==== Upgrading R packages ====
# pacman -S gcc-fortran
+
===== Within a R session =====
 +
> update.packages(ask=FALSE)
 +
Or when you also need to rebuild packages which were built for an older version:
 +
> update.packages(ask=FALSE,checkBuilt=TRUE)
 +
Or when you also need to select a specific mirror (https://cran.r-project.org/mirrors.html) to download the packages from (changing the url as need):
 +
> update.packages(ask=FALSE,checkBuilt=TRUE,repos="https://cran.cnr.berkeley.edu/")
 +
{{Tip|upgrading packages from your R session can quickly be a pain if you have too many loaded packages at start up. For packages to be upgraded, they cannot be loaded, so do not load packages from your Rprofile.
 +
}}
  
=== Installing R packages ===
+
===== Within a shell =====
There are many add-on R packages, which can be browsed on [http://cran.r-project.org/ The R Website.]. They can be installed from within R using the R install.packages command. It is not necessary to be superuser or have root privileges when doing this -- R can install its packages locally for the individual user. This is the safest way to install R packages and won't conflict with the pacman package management.
+
You can use {{ic|Rscript}}, which comes with {{Pkg|r}} to update packages from a shell:
  
To set the location of your local R package library, create a {{ic|~/.Renviron}} file and set R_LIBS_USER:
+
{{bc|
 +
$ Rscript -e "update.packages()"}}
  
{{hc|~/.Renviron|
 
R_LIBS_USER&#61;/home/username/path/to/R/packages}}
 
  
== Running R ==
+
===Makevars===
R can be run from the command line, by using the R command:
+
The Makevars file can be used to set the default make options when installing packages. An example optimized Makevars file is as follow:
$ R
+
{{hc|~/.R/Makevars|2=
 +
CFLAGS=-O3 -Wall -pedantic -march=native -mtune=native -pipe
 +
CXXFLAGS=-O3 -Wall -pedantic -march=native -mtune=native -pipe
 +
}}
  
 
== Adding a graphical frontend to R ==
 
== Adding a graphical frontend to R ==
  
The linux version of R does not include a graphical user interface. However, third-party user interfaces for R are available, such as R commander and RKWard.  
+
R does not include a point-and-click graphical user interface for statistics or data manipulation. However, third-party user interfaces for R are available, such as R commander and RKWard.
  
 
=== R Commander frontend ===
 
=== R Commander frontend ===
R Commander is a popular user interface to R. There is no Arch linux package available to install R commander, but it is an R package so it can be installed easily from within R.  R Commander requires Tk:
+
R Commander is a popular user interface to R. There is no Arch linux package available to install R commander, but it is an R package so it can be installed easily from within R.  R Commander requires {{Pkg|tk}} to be [[install]]ed.
# pacman -S tk
 
  
 
To install R Commander, run 'R' from the command line. Then type:
 
To install R Commander, run 'R' from the command line. Then type:
Line 45: Line 157:
  
 
=== RKWard frontend ===
 
=== RKWard frontend ===
RKWard is an open-source frontend which allows for data import and browsing as well as running common statistical tests and plots. You can install {{AUR|rkward}} from [[Arch User Repository|AUR]].
+
RKWard is an open-source frontend which allows for data import and browsing as well as running common statistical tests and plots. You can install {{AUR|rkward}} from [[AUR]].
 +
 
 +
== Editors IDEs and notebooks with R support ==
  
 
=== Rstudio IDE ===
 
=== Rstudio IDE ===
 
RStudio an open-source R IDE. It includes many modern conveniences such as parentheses matching, tab-completion, tool-tip help popups, and a spreadsheet-like data viewer.
 
RStudio an open-source R IDE. It includes many modern conveniences such as parentheses matching, tab-completion, tool-tip help popups, and a spreadsheet-like data viewer.
  
Install {{AUR|rstudio-desktop-bin}} (binary version from the Rstudio project website) or {{AUR|rstudio-desktop-git}} (development version) from [[Arch User Repository|AUR]].
+
Install {{AUR|rstudio-desktop-bin}} (binary version from the Rstudio project website) or {{AUR|rstudio-desktop-git}} (development version) from [[AUR]].
 +
 
 +
The R library path is often configured with the R_LIBS environment variable. RStudio ignores this, so the user must set R_LIBS_USER in {{ic|~/.Renviron}}, as documented above.
 +
 
 +
=== Rstudio server ===
 +
 
 +
RStudio Server enables you to provide a browser based interface to a version of R running on a remote Linux server.
 +
 
 +
Install {{AUR|rstudio-server-git}}. The two main configuration files are {{ic|/etc/rstudio/rserver.conf}} and {{ic|/etc/rstudio/rsession.conf}}. They are not created during the install, so you will need to ''create'' and ''edit'' them. For information about configure options, please refer to [https://support.rstudio.com/hc/en-us/articles/200552306-Getting-Started rstudio getting started] documentation.
 +
 
 +
To start the server, please [[Systemd#Using_units|enable and start]] the  {{ic|rstudio-server.service}} unit file provided with the package.
 +
 
 +
=== Emacs Speaks Statistics ===
 +
[[Emacs]] users can interact with R via the {{AUR|emacs-ess}} package.
 +
 
 +
=== Nvim-R ===
 +
The {{AUR|nvim-r}} package allows {{Pkg|vim}} and {{Pkg|neovim}} users to code in R, including editing and rendering of R markdown (Rmd) files, execution of R code in a separate pane, inspection of variables, and integrated help panes.
 +
 
 +
=== Cantor ===
 +
{{Pkg|cantor}} is a notebook application developed by KDE that includes support for R.
 +
 
 +
=== Jupyter notebook ===
 +
{{Pkg|jupyter-notebook}} is a browser based notebook with support for many programming languages. R support can be added by installing the [https://github.com/IRkernel/IRkernel IRkernel].
 +
 
 +
== Tips and tricks ==
 +
 
 +
=== Optimized packages ===
 +
The numerical libraries that comes with the R (generic {{Pkg|blas}}, LAPACK) do not have multithreading capabilities. Replacing the reference {{Pkg|blas}} package with an optimized BLAS can produce dramatic speed increases for many common computations in R. See these threads for an overview of the potential speed increases:
 +
 
 +
* https://github.com/tmolteno/necpp/issues/18
 +
* http://blog.nguyenvq.com/blog/2014/11/10/optimized-r-and-python-standard-blas-vs-atlas-vs-openblas-vs-mkl/
 +
* https://freddie.witherden.org/pages/blas-gemm-bench/
 +
* http://nghiaho.com/?p=1726
 +
 
 +
==== OpenBLAS ====
 +
{{Pkg|openblas}} can replace the reference {{Pkg|blas}}. If you are using the regular {{Pkg|r}} package from [extra] no further configuration is needed; R is configured to use the system BLAS and will use OpenBLAS once it is installed.
 +
 
 +
==== Intel MKL ====
 +
'''If your processors are Intel''', you can use the [http://software.intel.com/en-us/intel-mkl Intel math Kernel Library]. The '''MKL''', beyond the capabilities of multithreading, also has specific optimizations for Intel processors. Keep in mind that they can [http://blog.revolutionanalytics.com/2015/10/edge-cases-in-using-the-intel-mkl-and-parallel-programming.html potentially interfere with the standard R functionality for parallel processing].
 +
 
 +
Please first [[Install]] the {{AUR|intel-mkl}} package available from [[AUR]], then the {{AUR|r-mkl}} package.
 +
 
 +
{{Note|
 +
* if you install the {{AUR|r-mkl}} with '''R''' already installed, you will be prompted to remove '''R'''. Once '''r-mkl''' is installed, please run on '''R''' console the following command :
 +
{{ic|1=> update.packages(checkBuilt=TRUE)}}
 +
* here are elapsed time in sec from computing 15 tests with default GCC build and icc/MKL build: ''274.93 sec'' for GCC build, ''21.01 sec'' for icc/MKL build. See [https://stat.ethz.ch/pipermail/r-help/2014-September/421574.html this post] for more information.
 +
}}
 +
 
 +
==== intel-advisor-xe ====
 +
[http://software.intel.com/en-us/intel-advisor-xe intel-advisor] delivers top application performance with C, C++ and Fortran compilers, libraries and analysis tools.
 +
 
 +
Install the {{AUR|intel-advisor-xe}}{{Broken package link|package not found}} package.
 +
 
 +
=== Set CRAN mirror across R sessions ===
 +
 
 +
Instead of having R ask which CRAN mirror to use every time you install or update a package, you can set the mirror in the Rprofile file. https://cloud.r-project.org/ should be a good default for everywhere:
 +
 
 +
{{hc|head=~/.Rprofile|
 +
output=
 +
## Set CRAN mirror:
 +
local({
 +
  r <- getOption("repos")
 +
  r["CRAN"] <- "https://cloud.r-project.org/"
 +
  options(repos = r)
 +
})
 +
}}
 +
 
 +
== See also ==
 +
 
 +
* [https://www.r-project.org/ Official website]
 +
* [http://www.rseek.org/ RSeek] A Google Custom Search Engine for R related material.
 +
* [http://r4ds.had.co.nz/ R for Data Science] Online version of a CCA licensed book written by Garrett Grolemund and Hadley Wickham from RStudio, 2017.
 +
* [https://www.r-bloggers.com/ R-bloggers] Aggregation site for (English) blogs related to R.
 +
* [https://www.reddit.com/r/Rlanguage/ /r/Rlanguage on Reddit] There are several R related Subreddits, each one provides links to the others.

Latest revision as of 07:25, 20 October 2018

R is a "free software environment for statistical computing and graphics."[1]

Installation

Install the r package. The installation of external packages within the R environment may require gcc-fortran.

Usage

To start a R session, open your terminal and type this command:

$ R
Note:
  • Make sure to use a capital R for the command. Note that some shells use the lowercase r command to repeat the last entered command. Once in your R session, the prompt will change to >
  • site refers to system-wide in R Documentation

Run ?Startup to read the documentation about system file configuration, help() for the on-line help,help.start() for the HTML browser interface to help, demo() for some demos and q() to close the session and quit.

When closing the session, you will be prompted : Save workspace Image ?[y/n/c]. The workspace is your current working environment and include any user-defined objects, functions. The saved image is stored in .RData format and will be automatically reloaded the next time R is started. You can manually save the workspace at any time in the session with the save.image(image.RData) command, save as many images as you want (eg : image1.RData, image2.RData). You can load image with the load.image(image.RData) command at any time of your session.

Tip:
  • Tired of R's verbose startup message ? Then start R with the --quiet command-line option ($ R --quiet). You can add alias R="R --quiet" in one of your Startup files.
  • Running R from the command line will set R's working directory to the current directory. Opening the R GUI will set R's working directory to $HOME, unless explicitly defined in your configuration files (.Renviron or .Rprofile).

Configuration

Whenever R starts, its configuration is controlled by several files. Please refer to Initialization at Start of an R Session to get a detailed understanding of startup process.

Environment

R first loads site and user environment variable files. The name of the site file is controlled by the Environment variables R_ENVIRON if it exists, and defaults to /etc/R/.Renviron. The name of the user file is specified by R_ENVIRON_USER. If that is unset, it defaults to .Renviron in the curent working directory or if it exists, and ~/.Renviron otherwise.

Most important variables can be found on Environment Variables R Documentation.

You may disable loading environment files with --no-environ

Lines in Renviron file should be either comment lines starting with # or lines of the form name=value. Here is a very basic .Renviron:

.Renviron
R_HOME_USER = /path/to/your/r/directory
R_PROFILE_USER = ${HOME}/.config/r/.Rprofile
R_LIBS_USER = /path/to/your/r/library
R_HISTFILE = /path/to/your/filename.Rhistory                                             # Do not forget to append the .Rhistory
MYSQL_HOME = /var/lib/mysql


Profile

R then loads an Rprofile, which contains R code that is executed. These files are read in the following order of preference (only one file is loaded):

1. A file specified by the environment variable R_PROFILE_USER.

2. .Rprofile in the current working directory.

3. $HOME/.Rprofile.

An .Rprofile can contain arbitrary R code, though best practice suggests that one should not load packages at startup, as this hinders package upgrades and reproducibility.

~/.Rprofile
# The .First function is called after everything else in .Rprofile is executed
.First <- function() {
  # Print a welcome message
  message("Welcome back ", Sys.getenv("USER"),"!\n","working directory is:", getwd())
}

options(digits = 12)                                          # number of digits to print. Default is 7, max is 15
options(stringsAsFactors = FALSE)                             # Disable default conversion of character strings to factors
options(show.signif.stars = FALSE)                            # Don't show stars indicating statistical significance in model outputs
error <- quote(dump.frames("${R_HOME_USER}/testdump", TRUE))  # post-mortem debugging facilities

You can add more global options to customize your R environment. See this post for more examples of user configurations.

Locale

Aspects of the Locale are accessed by the functions Sys.getlocale and Sys.localeconv within the R session. Locales will be the one defined in your system.

Managing R packages

There are many add-on R packages, which can be browsed on The R Website..

Note: Some R packages link to files provided by system packages. These packages will need to be reinstalled when these files are updated.

With pacman

There are some packages available on the AUR with the prefix r-. You can mix and match installing R packages with pacman and through R (below), but if you do so you should let pacman manage system packages (those that reside at /usr/lib/R/library, and let R manage user-installed packages elsewhere (e.g. ~/R/library).

With R

Packages can be installed from within R using the install.packages(c("pkgname")) command. You should use a local library and let pacman manage files that reside under /usr/lib/R/library.

Note:
  • install.packages() requires tk to be installed for selecting mirrors. Try installing this package if you see:

Error: .onLoad failed in loadNamespace() for 'tcltk', details (...)

Within your R session, run this command to check that your user library exists and is set correctly:

> Sys.getenv("R_LIBS_USER")
[1] "/path/to/directory/R/packages"

Alternatively, you may install from the command line like so:

$ R CMD INSTALL -l $R_LIBS_USER pkg1 pkg2 ...

Upgrading R packages

Within a R session
> update.packages(ask=FALSE)

Or when you also need to rebuild packages which were built for an older version:

> update.packages(ask=FALSE,checkBuilt=TRUE)

Or when you also need to select a specific mirror (https://cran.r-project.org/mirrors.html) to download the packages from (changing the url as need):

> update.packages(ask=FALSE,checkBuilt=TRUE,repos="https://cran.cnr.berkeley.edu/")
Tip: upgrading packages from your R session can quickly be a pain if you have too many loaded packages at start up. For packages to be upgraded, they cannot be loaded, so do not load packages from your Rprofile.
Within a shell

You can use Rscript, which comes with r to update packages from a shell:

$ Rscript -e "update.packages()"


Makevars

The Makevars file can be used to set the default make options when installing packages. An example optimized Makevars file is as follow:

~/.R/Makevars
CFLAGS=-O3 -Wall -pedantic -march=native -mtune=native -pipe
CXXFLAGS=-O3 -Wall -pedantic -march=native -mtune=native -pipe

Adding a graphical frontend to R

R does not include a point-and-click graphical user interface for statistics or data manipulation. However, third-party user interfaces for R are available, such as R commander and RKWard.

R Commander frontend

R Commander is a popular user interface to R. There is no Arch linux package available to install R commander, but it is an R package so it can be installed easily from within R. R Commander requires tk to be installed.

To install R Commander, run 'R' from the command line. Then type:

> install.packages("Rcmdr", dependencies=TRUE)

This can take some time.

You can then start R Commander from within R using the library command:

> library("Rcmdr")

RKWard frontend

RKWard is an open-source frontend which allows for data import and browsing as well as running common statistical tests and plots. You can install rkwardAUR from AUR.

Editors IDEs and notebooks with R support

Rstudio IDE

RStudio an open-source R IDE. It includes many modern conveniences such as parentheses matching, tab-completion, tool-tip help popups, and a spreadsheet-like data viewer.

Install rstudio-desktop-binAUR (binary version from the Rstudio project website) or rstudio-desktop-gitAUR (development version) from AUR.

The R library path is often configured with the R_LIBS environment variable. RStudio ignores this, so the user must set R_LIBS_USER in ~/.Renviron, as documented above.

Rstudio server

RStudio Server enables you to provide a browser based interface to a version of R running on a remote Linux server.

Install rstudio-server-gitAUR. The two main configuration files are /etc/rstudio/rserver.conf and /etc/rstudio/rsession.conf. They are not created during the install, so you will need to create and edit them. For information about configure options, please refer to rstudio getting started documentation.

To start the server, please enable and start the rstudio-server.service unit file provided with the package.

Emacs Speaks Statistics

Emacs users can interact with R via the emacs-essAUR package.

Nvim-R

The nvim-rAUR package allows vim and neovim users to code in R, including editing and rendering of R markdown (Rmd) files, execution of R code in a separate pane, inspection of variables, and integrated help panes.

Cantor

cantor is a notebook application developed by KDE that includes support for R.

Jupyter notebook

jupyter-notebook is a browser based notebook with support for many programming languages. R support can be added by installing the IRkernel.

Tips and tricks

Optimized packages

The numerical libraries that comes with the R (generic blas, LAPACK) do not have multithreading capabilities. Replacing the reference blas package with an optimized BLAS can produce dramatic speed increases for many common computations in R. See these threads for an overview of the potential speed increases:

OpenBLAS

openblas can replace the reference blas. If you are using the regular r package from [extra] no further configuration is needed; R is configured to use the system BLAS and will use OpenBLAS once it is installed.

Intel MKL

If your processors are Intel, you can use the Intel math Kernel Library. The MKL, beyond the capabilities of multithreading, also has specific optimizations for Intel processors. Keep in mind that they can potentially interfere with the standard R functionality for parallel processing.

Please first Install the intel-mklAUR package available from AUR, then the r-mklAUR package.

Note:
  • if you install the r-mklAUR with R already installed, you will be prompted to remove R. Once r-mkl is installed, please run on R console the following command :

> update.packages(checkBuilt=TRUE)

  • here are elapsed time in sec from computing 15 tests with default GCC build and icc/MKL build: 274.93 sec for GCC build, 21.01 sec for icc/MKL build. See this post for more information.

intel-advisor-xe

intel-advisor delivers top application performance with C, C++ and Fortran compilers, libraries and analysis tools.

Install the intel-advisor-xeAUR[broken link: package not found] package.

Set CRAN mirror across R sessions

Instead of having R ask which CRAN mirror to use every time you install or update a package, you can set the mirror in the Rprofile file. https://cloud.r-project.org/ should be a good default for everywhere:

~/.Rprofile
## Set CRAN mirror:
local({
  r <- getOption("repos")
  r["CRAN"] <- "https://cloud.r-project.org/"
  options(repos = r)
})

See also

  • Official website
  • RSeek A Google Custom Search Engine for R related material.
  • R for Data Science Online version of a CCA licensed book written by Garrett Grolemund and Hadley Wickham from RStudio, 2017.
  • R-bloggers Aggregation site for (English) blogs related to R.
  • /r/Rlanguage on Reddit There are several R related Subreddits, each one provides links to the others.