Meta Data

Rating R Packages

Quickly rating some R packages I like with R

Robert McDonnell

2 minute read

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 2016-06-24 295115 1847 728 0.2 0 1 219 tidyr 2017-05-15 147418 469 168 0.2 0 1 58 tidyRSS 2017-03-01 319 10 2 0.4 0.7 1 3 congressbr 2017-04-30 556 1 rstan 2017-04-19 9583 341 132 0.1 0.1 3 66 rjags 2016-02-19 12638 2 electionsBR 2016-12-13 664 17 4 0.7 3.6 1 7 tmap 2017-05-11 4236 144 25 0 0.1 2 16 Nice table.