Practical R for Mass Communication and Journalism

People working in the media deal with data constantly. Journalists who are interested in improving their data skills will find this book useful. The book will concentrate on teaching R and will not go into statistical details. Data sets and projects chosen for the book are especially important in the journalism market.

Introduction Why programming? Why R? Is this book for you? Get Started With R in a Few Easy Steps What we'll cover Download R and RStudio A brief introduction to RStudio Try out the console Install packages Additional infrastructure Getting help with packages and functions RStudio keyboard shortcuts Additional files available online Wrap-Up Additional resources See How Much You Can Do in a Few Lines of Code Packages needed this chapter What we'll cover Simple stock market graphing Download and graph a city's median income So many packages! Running functions without loading packages Comparing one city's data to the US median Run a remote script to make an interactive map Bonus map: Mapping income data Wrap-Up Additional resources Import Data into R What we'll cover Packages needed this chapter The magic of rio Import data from packages What's a data frame? And what can you do with one? Easy sample data Exporting data Additional resources Basic Data Exploration Project: Weather data What we'll cover Packages needed this chapter Download this book's files Data summaries Data `interviews' Slicing and dicing your data set More sub setting with dplyr Wrap-Up Additional resources Beginning data visualization Project: More weather data What we'll cover: How to Packages needed this chapter Answer questions with graphics Easy visualizations in or lines of code Some basic graphs The full power of ggplot Basic ggplot customizations Code snippets to the rescue Presentation-quality graphics Comment your code Wrap-up Additional resources Two or more data sets Project: Multiple files of US airline on-time data What we'll cover Packages needed this chapter Add one table to the bottom of another What's a list, and how do operate on one? lapply here () you are! Wrap-up Exercise Answer Additional resources Analyze data by groups Project: Airline on-time data analysis (cont) What we'll cover Packages needed this chapter Lookup tables Beware of missing values Bar graph of raw data Wrap up Additional resources Graphing by Group Project: Visualizing airline on-time data What we'll cover Packages needed this chapter Facets Housing prices by state Geofacets Customizing colors Color palettes Other packages that extend ggplot functionality Wrap-up Additional Resources Exercise answer Write your own R functions What we'll cover Packages needed this chapter Function basics seq() If-then-else if statements for vectors A taste of testing Next steps for your functions More Resources Exercise Answer Exercise Answer Exercise Maps in R Map projects this chapter Skills we'll cover Importing shape files into R Import data for mapping An even easier way to pull US Census data Interactive maps with tmap Importing and joining data Leaflet and points on a map geocoding and R's paste () function Time to geocode with R (or maybe without) Mapping points with leaflet Points and polygons on a single map Mapping new political boundaries with leaflet Inspiration: Washington Post investigation Wrap-up Additional resources Putting it all Together: R on Election Day Project: Election data What we'll cover Packages needed this chapter Election Day preparation Visualizing election results Graph for a smaller set of results plotly Other interactive alternatives Wrap-up (Non-election) inspiration Additional resources Date calculations Project: New York City restaurant inspections What we'll cover Packages needed this chapter Get started with dates in R Get NYC inspection data Wrap-up Inspiration Additional resources Help! My data's in the wrong format! Project: Election results in a PDF What we'll cover Packages needed this chapter Human vs machine optimizing The raw data Extracting data from PDFs Tidying the data Reshaping the data `Long' data back to `wide' Winners and runners-up Wrap-up Additional resource Using tabulizer to unlock the City Council data Integrate R With Your Storytelling Using R Markdown Project: Mixing text and R code about that snow data What we'll cover Packages needed this chapter R Markdown basics Create an R Markdown document R Markdown text syntax R code chunks Adding R code to run Add an R-generated graph Setting option options Mixing R within text Even more options Repeatability with R Markdown parameters Wrap-up Additional resources Simple Web scraping Project: Download RStudio PDF cheat sheets What we'll cover Packages needed this chapter Step: Follow the rules with robotstxt Step: Get a list of links Step: Download files Wrap-Up Additional resources An R project from start to finish Project: Local political contribution and election data What we'll cover Packages needed this chapter Get the data, make it ready for analysis Standardizing multiple versions of the same name Making data frames Analyzing and graphing the results Visualizing results Consider R Markdown Additional resources Additional resources More functions, packages and tools worth a look Stories done with R Tutorials Social media, communities, and Web resources Appendix A Online: How do I Appendix B Online: Functions Appendix C Online: Packages