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Exploring the tidyverse in R

This is the repo for the one-day workshop "Exploring the tidyverse in R" taught at NICAR's 2020 conference in New Orleans, LA.

If you want to trace the provenance of these materials... Originally, materials were by Hadley Wickham. For 2019, the materials were tailored to a data journalism audience and one-day time frame, including new training data and materials on visualization from Andrew Ba Tran and his R for Journalists, Aaron Kessler's materials and training sequences on transforming data, and Olga Pierce's materials on modeling and statistics. For 2020, we've edited and refined these materials to be even better, and brought in Amelia McNamara.

The course has three main modules:

A. Transforming Data

B. Visualizing Data

C. Modeling Data

This workshop is designed for people who are familiar with some R and want to learn how to achieve their data analysis goals the "tidy" way.

You will learn how to visualize, transform, and model data in R and work with date-times, character strings, and untidy data formats. Along the way, you will learn and use many packages from the tidyverse including ggplot2, dplyr, tidyr, readr, purrr, tibble, stringr, lubridate, and forcats.

Software requirements

You'll need the following packages:

install.packages(c("tidyverse", "lubridate", "janitor", "rmarkdown", "usethis", "leaflet", "htmltools"))

Then you can grab a local copy of all the slides, code, data, and cheatsheets with:


To get back to this project later, double-click on "data-science-in-the-tidyverse.Rproj".

Intro slides:


Creative Commons License

Data Science in the tidyverse by Charlotte Wickham is licensed under a Creative Commons Attribution 4.0 International License. Based on a work at


I forked this repo from Aaron Kessler's NICAR 2019 repo, who forked from Hadley Wickham based on his session at NICAR 2018, who in turn forked it from Charlotte Wickham, who forked it from RStudio. Thanks to Charlotte and Garrett for creating the slides and cheatsheet materials.


A substantially modified one-day workshop at NICAR 2020 on learning the R tidyverse packages






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