index.Rmd

--- 
title: "Data Wrangling with R"
author: "Claudia A Engel"
date: "Last updated: `r format(Sys.time(), '%B %d, %Y')`"
site: bookdown::bookdown_site
output: bookdown::gitbook
documentclass: book
bibliography: [book.bib, packages.bib]
biblio-style: apalike
link-citations: yes
github-repo: cengel/R-data-wrangling
description: "Workshop materials for Data Wrangling with R"
---


# Prerequisites and Preparations {-}

- You should have some **basic knowledge** of R, and be familiar with the topics covered in the [Introduction to R](https://cengel.github.io/R-intro/).
- Have a recent version of [R](https://cran.r-project.org/) and [RStudio](https://www.rstudio.com/) installed. 
- Install and load the `tidyverse` package.
```{r, eval=FALSE, purl = FALSE}
install.packages("tidyverse")  
library(tidyverse)
```
- Create a new RStudio project `R-data-ws` in a new folder `R-data-ws`. Download both CSV files into a subdirectory called `data` like this:
- Download `MS_trafficstops_bw_age.csv`:
```{r, eval=FALSE, purl = FALSE}
download.file("http://bit.ly/MS_trafficstops_bw_age",
              "data/MS_trafficstops_bw_age.csv")
```
- Download `MS_acs2015_bw.csv`:
```{r, eval=FALSE, purl = FALSE}
download.file("http://bit.ly/MS_acs_2015_bw",
              "data/MS_acs2015_bw.csv")
```


## References {-}
Boehmke, Bradley C. (2016) Data Wrangling with R
http://link.springer.com/book/10.1007%2F978-3-319-45599-0

Grolemund, G & Wickham, H (2017): R for Data Science http://r4ds.had.co.nz

Wickham, H. (2014): Tidy Data https://www.jstatsoft.org/article/view/v059i10


## Acknowledgements {-}
Part of the materials for this tutorial are adapted from http://datacarpentry.org and http://softwarecarpentry.org.