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title: Other Resources
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## Configuring R and RStudio (Linux)

- [Installing xlsx and XML packages on Debian Wheezy](http://allanino.me/blog/programming/installing-some-r-packages/)
- [Rscript to customize R environment](http://bit.ly/r-customize-script) - Installs packages used in the specialization.
- [Installing Some Basic R Packages in Ubuntu; Ibrahim El Merehbi](http://elmerehbi.wordpress.com/2014/09/09/installing-some-basic-r-packages-in-ubuntu)
- [Using Projects in RStudio](https://support.rstudio.com/hc/en-us/articles/200526207-Using-Projects)
- [Using Version Control with RStudio](https://support.rstudio.com/hc/en-us/articles/200532077-Version-Control-with-Git-and-SVN)

### Ignoring R & RStudio files
- [gitignore template for R](https://github.com/github/gitignore/blob/master/R.gitignore) (source:[gitignore](https://github.com/github/gitignore))
- [Github Help - Using Git / Ignoring files](https://help.github.com/articles/ignoring-files/)

## Troubleshooting
- [Windows batch file to work around RStudio startup issues](https://github.com/stepds/contrib-DataScienceSpecialization/blob/master/README.md)

## Pre-built virtual machines for R development.
- [Here's a pre-built lightweight Linux machine with R and RStudio already installed](https://github.com/queirozfcom/r-box). You just need to install [vagrant](https://www.vagrantup.com/downloads.html), download (or clone) the github repository and you'll get a clean ubuntu machine with the tools you'll need for the assignments. 

- [Data Science Toolbox](http://datasciencetoolbox.org/) - A virtual environment that allows you to start doing data science in a matter of minutes.

- [Virtual machine with RStudio server and github setup](https://github.com/tboloo/vagrant-rstudio) - A VirtualBox, Vagrant & chef-solo managed virtual machine which provides RStudio server with git & github setup