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https://github.com/kjhealy/socviz

Support files for a data visualization course and book
https://github.com/kjhealy/socviz

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Support files for a data visualization course and book

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README 

        
---

output: github_document

---



```{r, echo = FALSE}

knitr::opts_chunk$set(

  collapse = TRUE,

  echo = TRUE,

  comment = "#>",

  fig.path = "inst/assets/README-"

  )



get_badge <- function (pkg, type = c("last-month", "last-week", "grand-total"), 

    color = "green") 

{

    type <- match.arg(type)

    svg <- paste0("http://cranlogs.r-pkg.org/badges/", type, 

        "/", pkg, "?color=", color)

    url <- paste0("https://cran.r-project.org/package=", pkg)

    placeholder <- "CRAN link"

    paste0("[![](", svg, ")](", url, ")")

}



```



# socviz 



[![R build status](https://github.com/kjhealy/socviz/workflows/R-CMD-check/badge.svg)](https://github.com/kjhealy/socviz/actions)



This is an R package of datasets, functions, and course materials to go along with the book _[Data Visualization: A Practical Introduction](https://amzn.to/2vfAixM)_ (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](https://amzn.to/2vfAixM)_ (`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](http://rstudio.com) project consisting of a nine [R Markdown](http://rmarkdown.rstudio.com) 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](https://cran.r-project.org/bin/macosx/), [Windows](https://cran.r-project.org/bin/windows/) or [Linux](https://cran.r-project.org/bin/linux/), as appropriate. Then download and install [RStudio](http://rstudio.com/download/). Launch RStudio and then type the following code at the Console prompt (`> `), hitting return at the end of each line:



```{r, eval = FALSE}



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:



```{r, eval = FALSE}



devtools::install_github("kjhealy/socviz")



```



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



```{r, eval = FALSE}

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:



```{r, eval = FALSE}



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:



```{r, eval = FALSE}



setup_course_notes(folder = "~/Documents")



```



## More about the Datasets and Functions



The included datasets and functions are documented at .