The new rOpenSci package packagemetrics is a new ‘meta’ package for R with info on packages: dependencies, how long issues take to be resolved, how many watchers on GitHub, and more. Let’s take a look at a few packages I use and some of my own. Install:
install.packages("formattable")
devtools::install_github("ropenscilabs/packagemetrics")Then load the packages we’re going to use (I liked the table they have in their README, so I thought I’d keep with that style):
library(formattable)
library(packagemetrics)
library(dplyr)Next, let’s get the packages I’m interested in and make our nice table:
packages <- list("dplyr", "tidyr", "tidyRSS",
"congressbr", "rstan", "rjags",
"electionsBR", "tmap")
pd <- purrr::map(packages, combine_metrics) %>%
data.table::rbindlist() %>%
select(package, published, dl_last_month, stars, forks,
last_commit, last_issue_closed,
depends_count, watchers) %>%
mutate(last_commit = round(last_commit, 1),
last_issue_closed = round(last_issue_closed, 1))
pd[is.na(pd)] <- ""
formattable(pd, list(
package = formatter("span",
style = x ~ style(font.weight = "bold")),
contributors = color_tile("white","#1CC2E3"),
depends_count = color_tile("white", "#1CC2E3"),
reverse_count = color_tile("white", "#1CC2E3"),
tidyverse_happy = formatter("span",
style = x ~ style(color = ifelse(x, "purple","white")),
x ~ icontext(ifelse(x, "glass","glass"))),
vignette = formatter("span",
style = x ~ style(color = ifelse(x, "green","white")),
x ~ icontext(ifelse(x, "ok","ok"))),
has_tests = formatter("span",
style = x ~ style(color = ifelse(x, "green","red")),
x ~ icontext(ifelse(x, "ok","remove"))),
dl_last_month = color_bar("#56A33E"),
forks = color_tile("white", "#56A33E"),
stars = color_tile("white", "#56A33E"),
last_commit = color_tile("#F06B13","white", na.rm=T),
last_issue_closed = color_tile("#F06B13","white", na.rm=T)
))| package | published | dl_last_month | stars | forks | last_commit | last_issue_closed | depends_count | watchers |
|---|---|---|---|---|---|---|---|---|
| dplyr | 2019-02-15 | 759338 | 2864 | 1049 | 0 | 0 | 1 | 258 |
| tidyr | 2019-03-01 | 477218 | 716 | 282 | 0.1 | 0 | 1 | 73 |
| tidyRSS | 2019-03-05 | 1215 | 29 | 10 | 0.9 | 0.6 | 1 | 5 |
| congressbr | 2019-02-17 | 498 | 1 | |||||
| rstan | 2018-11-07 | 33293 | 541 | 179 | 0 | 3 | 79 | |
| rjags | 2018-10-19 | 15799 | 2 | |||||
| electionsBR | 2017-06-06 | 398 | 32 | 9 | 2 | 1 | 9 | |
| tmap | 2019-01-05 | 18297 | 312 | 58 | 0.2 | 0.2 | 2 | 26 |
Nice table. It’s not perfect – maybe they still have some bugs to work out – congressbr is missing watchers and stars, but this is a nice little package. Still, there are so many packages out there that I still use them based on cool examples I see, either on blogs, twitter, or in academic papers. I’ve never much used the CRAN Task Views and I doubt I’ll use packagemetrics much, but it’s interesting for those who get their R this way.