A Criminologist's Guide to R Crime by the Numbers
A Criminologist's Guide to R: Crime by the Numbers introduces the programming language R and covers the necessary skills to conduct quantitative research in criminology. By the end of this book, a person without any prior programming experience can take raw crime data, be able to clean it, visualize the data, present it using R Markdown, and change it to a format ready for analysis. A Criminologist's Guide to R focuses on skills specifically for criminology such as spatial joins, mapping, and scraping data from PDFs, however any social scientist looking for an introduction to R for data analysis will find this useful.
- Introduction to RStudio including how to change user preference settings.
- Basic data exploration and cleaning – subsetting, loading data, regular expressions, aggregating data.
- Graphing with ggplot2.
- How to make maps (hotspot maps, choropleth maps, interactive maps).
- Webscraping and PDF scraping.
- Project management – how to prepare for a project, how to decide which projects to do, best ways to collaborate with people, how to store your code (using git), and how to test your code.
Chapter 1 A soup to nuts project example
Chapter 2 Introduction to R and Rstudio
Chapter 3 Data types and structures
Chapter 4 Reading and writing Data
Chapter 5 Mise en place
Chapter 6 Collaboration
Chapter 7 R Markdown
Chapter 8 Testing your code
Chapter 9 Git
Chapter 10 Subsetting: Making big things small
Chapter 11 Exploratory data analysis
Chapter 12 Regular Expressions
Chapter 13 Reshaping data
Chapter 14 Graphing with ggplot2
Chapter 15 More graphing with ggplot2
Chapter 16 Hotspot maps
Chapter 17 Choropleth maps
Chapter 18 Interactive maps
Chapter 19 Webscraping with rvest
Chapter 20 Functions
Chapter 21 For Loops
Chapter 22 Scraping tables from PDFs
Chapter 23 More scraping tables from PDFs
Chapter 24 Geocoding
"While many introductory R books use heterogeneous examples, here, the author did a great job introducing the R programming language using examples from criminology in a homogenous way. This book also offers a valuable compendium of crime related datasets for those already familiar programming in R. Specially, for graduate students, researchers, and data scientists, that wish to conduct more complex analyses on these types of data."
- Enrique Garcia-Ceja, Tecnologico de Monterrey, Mexico, Technometrics, November 2023.