31 January 2013

repmis: misc. tools for reproducible research in R

I've started to put together an R package called repmis. It has miscellaneous tools for reproducible research with R. The idea behind the package is to collate commands that simplify some of the common R code used within knitr-type reproducible research papers.

It's still very much in the early stages of development and has two commands:

  • LoadandCite: a command to load all of the R packages used in a paper and create a BibTeX file containing citation information for them. It can also install the packages if they are on CRAN.
  • source_GitHubData: a command for downloading plain-text formatted data stored on GitHub or at any other secure (https) URL.

I've written about why you might want to use source_GitHubData before (see here and here).

You can use LoadandCite in a code chunk near the beginning of a knitr reproducible research document to load all of the R packages you will use in the document and automatically generate a BibTeX file you can draw on to cite them. Here's an example:

# Create vector of package names
PackagesUsed <- c("knitr", "xtable")

# Load and Cite
repmis::LoadandCite(PackagesUsed, file = "PackageCitations.bib") 

LoadandCite draws on knitr's write_bib command to create the bibliographies, so each citation is given a BibTeX key like this: R-package_name. For example the key for the xtable package is R-xtable. Be careful to save the citations in a new .bib file, because LoadandCite overwrites existing files.

Citation of R packages is very inconsistent in academic publications. Hopefully by making it easier to cite packages more people will do so.


Instructions for how to install repmis are available here.

Please feel free to fork the package and suggest additional commands that could be included.

6 January 2013

source_GitHubData: a simple function for downloading data from GitHub into R

Update 31 January: I've folded source_GitHubData into the repmis packaged. See this post.

Update 7 January 2012: I updated the internal workings of source_GitHubData so that it now relies on httr rather than RCurl. Also it is more directly descended from devtool's source_url command.

This has two advantages.

  • Shortened URL's can be used instead of the data sets' full GitHub URL,
  • The ssl.verifypeer issue is resolved. (Though please let me know if you have problems).

The post has been rewritten to reflect these changes.

In previous posts I've discussed how to download data stored in plain-text data files (e.g. CSV, TSV) on GitHub directly into R.

Not sure why it took me so long to get around to this, but I've finally created a little function that simplifies the process of downloading plain-text data from GitHub. It's called source_GitHubData. (The name mimicks the devtools syntax for functions like source_gist and source_url. The function's syntax is actually just a modified version of source_url.)

The function is stored in a GitHub Gist HERE (it's also at the end of this post). You can load it directly into R with devtools' source_gist command.

Here is an example of how to use the function to download the electoral disproportionality data I discussed in an earlier post.

# Load source_GitHubData

# The functions' gist ID is 4466237

# Create Disproportionality data UrlAddress object
# Make sure the URL is for the "raw" version of the file
# The URL was shortened using bitly
UrlAddress <- "http://bit.ly/Ss6zDO"

# Download data
Data <- source_GitHubData(url = UrlAddress)

# Show Data variable names

## [1] "country"            "year"               "disproportionality"

There you go.

Note that the the function is set by default to load comma-separated data (CSV). This can easily be changed with the sep argument.