Anonymized package and R language downloads from the RStudio CRAN mirror.
r-downloads.csv
- R language downloads from RStudio CRAN mirror on last TidyTuesday for October 23, 2018.r_downloads_year.csv
- A year's worth of R language downloads from RStudio CRAN mirror between October 20, 2017 and October 20, 2018.
Header | Description |
---|---|
date |
date of download (y-m-d) |
time |
time of download (in UTC) |
size |
size (in bytes) |
version |
R release version |
os |
Operating System |
country |
Two letter ISO country code. |
ip_id |
Anonymized daily ip code (unique identifier) |
Package downloads end up with MUCH larger metadata files and are a bit unwieldy to work with, but if you want to play around with them you can use a few ways to easily check!
- .csv.gz files (can be read directly into R via
readr::read_csv()
- Data back to Oct 2012
- Package and R-language downloads (anonymized)
# Set your range of dates
start <- as.Date('2012-10-01')
today <- as.Date('2018-10-27')
all_days <- seq(start, today, by = 'day')
year <- as.POSIXlt(all_days)$year + 1900
# combine dates into a character vector of dates
urls <- paste0('http://cran-logs.rstudio.com/', year, '/', all_days, '.csv.gz')
# Read directly into memory as dataframe
urls %>%
map_dfr(read_csv)
# Can use download.file to download instead of read into memory
- Extremely easy to use and small data files
- Let's you download by specific packages or look over small time-frames to see what were the most popular packages.
- Con: Aggregated data for the most part
installr::download_RStudio_CRAN_data
- Downloads data from RStudio CRAN anonymized logs via API call
- Has download and read function built in for working with CRAN log data