Big in Japan

[This article was first published on Gianluca Baio's blog, 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.

Inspired by this post on R-bloggers, I decided to check how BCEA was doing. Unfortunately, it does not feature in the top 100 most downloaded R packages. However, I think it’s doing well $-$ considering the book (which is the main medium of advertising of the package) has been out for only a few months (since October last year) and it’s kind of a specialised software, which basically you only need if you do health economic evaluations…

I’ve used some simple R code to download the log files containing all hits to since October of 2012. Once the files (in .csv format, compressed in .gz files, one per each day) are downloaded, I have R extract the original file and then create a table, only selecting the records for BCEA.

The resulting dataset contains the date(s) and time(s) in which the library has been downloaded from CRAN, some information about the R version and architecture of the person who has downloaded the package, as well as their country.

Overall, BCEA has been officially downloaded 862 times (I suppose I should have a big celebration as soon as I hit 1000); most of the times, the download was from a user in the US (185). Surprisingly, BCEA is big in Japan (135 downloads). I did not see this coming, I have to say, but 日本ありがとう$-$ that’s “thank you Japan”, for those of you who can’t speak Japanese (or can’t use Google Translate).

Here’s the (quickly prepared and hence not particularly elegant, nor necessarily super-efficient) code to download and format the data:
start <- as.Date('2012-10-01')
today <- as.Date('2013-06-12')
all_days <- seq(start, today, by = 'day')
year <- as.POSIXlt(all_days)$year + 1900
urls <- paste0('', year, '/', all_days, '.csv.gz')
file <- basename(urls)
download.file(urls[1], file[1])
data <- read.table(gzfile(file[1]),sep=",",header=TRUE)
data <- data[data$package=="BCEA",]
for (i in 2:length(urls)) {
download.file(urls[i], file[i])
tmp <- read.table(gzfile(file[i]),sep=",",header=TRUE)
tmp <- tmp[tmp$package=="BCEA",]
data <- rbind(data,tmp)
data <- na.omit(data)

To leave a comment for the author, please follow the link and comment on their blog: Gianluca Baio's blog. 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.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)