Site icon R-bloggers

Updates to repmis: caching downloaded data and Excel data downloading

[This article was first published on Christopher Gandrud (간드루드 크리스토파), and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Over the past few months I’ve added a few improvements to the repmis–miscellaneous functions for reproducible research–R package. I just want to briefly highlight two of them:

Both of these capabilities are in repmis version 0.2.9 and greater.

Caching

When working with data sourced directly from the internet, it can be time consuming (and make the data hoster angry) to repeatedly download the data. So, repmis’s source functions (source_data, source_DropboxData, and source_XlsxData) can now cache a downloaded data set by setting the argument cache = TRUE. For example:

DisData <- source_data("http://bit.ly/156oQ7a", cache = TRUE)

When the function is run again, the data set at http://bit.ly/156oQ7a will be loaded locally, rather than downloaded.

To delete the cached data set, simply run the function again with the argument clearCache = TRUE.

source_XlsxData

I recently added the source_XlsxData function to download Excel data sets directly into R. This function works very similarly to the other source functions. There are two differences:

  • You need to specify the sheet argument. This is either the name of one specific sheet in the downloaded Excel workbook or its number (e.g. the first sheet in the workbook would be sheet = 1).

  • You can pass other arguments to the read.xlsx function from the xlsx package.

Here’s a simple example:

RRurl <- 'http://www.carmenreinhart.com/user_uploads/data/22_data.xls'

RRData <- source_XlsxData(url = RRurl, sheet = 2, startRow = 5)

startRow = 5 basically drops the first 4 rows of the sheet.

To leave a comment for the author, please follow the link and comment on their blog: Christopher Gandrud (간드루드 크리스토파).

R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.