This is an R package of datasets, functions, and course materials to go along with the book Data Visualization: A Practical Introduction (Princeton University Press, 2019).

## What’s in this Package

The socviz package contains about twenty five datasets and a number of utility and convenience functions. Most of them are used in Data Visualization: A Practical Introduction (http://socviz.co), and there are also a few others as well for self-learners and students to practice their skills on.

A course packet is also included. This is a zipped file containing an R Studio project consisting of a nine R Markdown documents that parallel the chapters in the book. They contain the code for almost all the figures in the book (and a few more besides). Some support files are also included, to help demonstrate things like reading in your own data locally in R.

## Installation

To install the package, you can follow the instructions in the Preface to the book. Alternatively, first download and install R for MacOS, Windows or Linux, as appropriate. Then download and install RStudio. Launch RStudio and then type the following code at the Console prompt (>), hitting return at the end of each line:



my_packages <- c("tidyverse", "fs", "devtools")
install.packages(my_packages)

install.packages("socviz")


To install the development version of socviz, instead of install.packages("socviz") do the following:


devtools::install_github("kjhealy/socviz")


Once everything has downloaded and been installed (which may take a little while), load the socviz package:

library(socviz)


## The Course Packet

The supporting materials are contained in a compressed .zip file. To extract them to your Desktop, make sure the socviz package is loaded as described above. Then do something like this:


setup_course_notes(folder = "~/Desktop")


You can choose the destination folder, but you must supply one. Here, the dataviz_course_notes.zip file will be copied to your Desktop, and uncompressed there into a folder called dataviz_course_notes. Open the folder, and double-click the file named dataviz.Rproj to launch the project as a new RStudio session. If you want to uncompress the file somewhere other than your Desktop, e.g. your Documents folder, you can do this:


setup_course_notes(folder = "~/Documents")


## More about the Datasets and Functions

The included datasets and functions are documented at http://kjhealy.github.io/socviz/reference/.