2 minute read

A few week’s ago, RWeekly featured Erin Grand’s post: Twitter’s Favorite Lesser Known Packages. There was a plethora of responses where R-users shared packages/functions that they have found to be useful. I was inspired to and wanted to share a few of my favorites.


One of my favorite R packages actually only has two functions. beepr is a package that plays notification sounds. I often add beep() to the end of long scripts and jobs running in the background. Instead of checking my RStudio session every so often I can simply wait for my computer to ping.

Actually, on a few occasions I’ve used R as a timer:


# Set a one minute timer
Sys.sleep(60); beep()

Of course, there are other packages with similar utility. This StackOverflow question includes various other packages, functions, and snippets that provide different notification methods.


pacman is a package that I found on some random Gist.

The package has many useful functions, but I have found the most use out of p_load(). p_load is a wrapper function for base functions library and require. Instead of starting a script with install.packages() and a long series of library() commands, p_load() checks to see if the packages are installed, and attempts to install those that aren’t already from CRAN.

As an example, I could replace this:

# Install Packages
install.packages(c("dplyr", "tidyr", "forcats", "readr", "ggplot2", "lubridate"))

# Load libraries

With this:

# Install pacman, if necessary
if(!require(pacman)) install.packages("pacman")

pacman::p_load(dplyr, tidyr, forcats, readr, ggplot2, lubridate)

This is very similar to the needs package, which I’ve noticed that John Burn-Murdoch uses for the majority of his scripts.


Finally, tictoc is a package I came across online only recently. tictoc provides timing functions that can be nested in code. I’m getting used to using timing utilities in my code, but for now I’ve found the simplest application is adding tic and toc to sections of my code:

# ---- Load library

# ---- Import data
tic("Section 1")
print("Import data... readr... readxl... RSQLite...")
toc(log = TRUE)
#> Section 1: 3.02 sec elapsed

# ---- Data cleaning
tic("Section 2")
print("Data munging, manipulation, dplyr, mutate, etc.")
toc(log = TRUE)
#> Section 2: 2.51 sec elapsed

# ---- Data viz
tic("Section 3")
print("Something with ggplot2")
toc(log = TRUE)
#> Section 3: 1.01 sec elapsed

# View tic log summary
# What sections took the longest?
#> [[1]]
#> [1] "Section 1: 3 sec elapsed"
#> [[2]]
#> [1] "Section 2: 2.52 sec elapsed"
#> [[3]]
#> [1] "Section 3: 1.02 sec elapsed"

There are some great resources online on how to use tictoc or other packages/functions that measure code running time. Here are a few I found interesting:

One of the great things about R is that there is pretty much a package for everything. I always enjoy learning about useful, fun, or cool-but-useless packages and functions. :wink: