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
library(devtools)

# The functions' gist ID is 4466237
source_gist("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
names(Data)


## [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.