R Packages

🧰 R Packages for Data Stewardship 📦

Welcome to the R Packages section of the DSU site! 🐟

Here you’ll find a curated set of R packages that support your work as a data steward or data producer within the Pacific Region Science Branch of Fisheries and Oceans Canada. 🧪🌊

tidyr

tidyr, an offering from the tidyverse is the speedy Swiffer mop to your messy data. It provides tools for following the ethos of tidy data, which holds the following tenets:

Each variable is a column; each column is a variable.
Each observation is a row; each row is an observation.
Each value is a cell; each cell is a single value.

For example, make your wide formatted data more tidy with pivot_longer() or deal with missing values with drop_na().

Want to load all the tidyverse packages at once?

Try library(tidyverse) to load all of those amazing tools in one line

ggplot2

ggplot2 is a powerful tool for data visualization offered under the tidyverse umbrella.

As any scientist knows, visualizing your data is just as important as generating it. After all, how can you communicate your results if they’re hidden away in a table?

The R graph gallery has countless of great examples of plots created with ggplot2. Check them out!

dplyr

Another tidyverse offering, dplyr is an essential package for data manipulation. Try out generating summary stats in a breeze with group_by() |> summarise() or join two datasets with a left_join().

arrow

arrow is an amazing tool for working with larger than memory data. R usually performs computations in RAM (your computer’s short term memory), but this can pose a problem for larger datasets. Arrow moves computations onto disk (your computer’s long term memory) to avoid this.

For a tutorial, see here