LearnR Sports Data Tutorials

Interactive R tutorials for SPMC350 at the University of Nebraska-Lincoln's College of Journalism and Mass Communications. These 37 lessons teach R programming, data analysis, and data visualization using real sports data.

What You'll Learn

R Fundamentals (Lessons 1–12) Working with data in R, filtering, mutating, aggregating, and joining datasets. Statistical concepts including significance testing, correlation, linear and multiple regression, residuals, and z-scores.

Data Visualization (Lessons 13–27) Creating and customizing charts with ggplot2: bar charts, stacked bars, waffle charts, line and step charts, slope charts, scatterplots, bubble charts, beeswarm plots, bump charts, dumbbell charts, tables, faceting, and arranging multiple plots.

Advanced Topics (Lessons 28–37) Finishing and publishing work: annotations, headlines, color, and finishing touches. Web scraping with rvest, text cleaning, clustering, simulations, and data joins.

Installation

You will need R and RStudio installed first.

Step 1 — Install required packages:

install.packages(c("tidyverse", "rmarkdown", "lubridate", "janitor", "cowplot", "learnr", "wehoop", "remotes", "devtools", "ggrepel", "ggbeeswarm", "ggtext", "rvest", "Hmisc", "cluster"))

Step 2 — Install ggbump:

devtools::install_github("mattwaite/ggbump")

Step 3 — Install the tutorials package:

devtools::install_github("mattwaite/SportsDataTutorials")

If prompted about installing newer versions of dependencies, decline.

Running a Tutorial

In the RStudio console, run:

learnr::run_tutorial("01-basics", package = "SportsDataTutorials")

Replace "01-basics" with the tutorial you want to open. Tutorials are numbered 01 through 37.