Intro to Tidy Data w/ R

WHO is this for?

• If you are new to R & are short-budgeted on time!
• If you'd like to start working with data in R w/o learning all the programming details first!!
• If you have a neat data set you'd like to explore and visualize!
• If you are a current R user but only familiar w/ base R!
• If you are unfamiliar with pipes
• If you have heard of tidyverse/dplyr/tidyr/tibble/ggplot but haven't had the chance to get started!

If any/all of this is true, this workshop might be for you!

WHAT we are planning!

• basics of tidyverse & ’tidy data’
• reshaping data with tidyr: gather, spread, separate, unite
• exploring data with dplyr: filter, select, mutate, transmute, arrange, summarise, group_by
• how tidy data talks to ggplot
• a quick summary of ggplot2
• finally, publication quality figures w/ R!

AGENDA
6:00–6:15 Meet & Greet | 🍕| Set-up
6:15–6:25 Who we are | Announcements | What's next
6:25–7:25 Workshop: Intro to Tidy Data w/ R
7:25–7:30 Any more Qs? How to reach us to continue this conversation!

To benefit most from this workshop

1. please bring your laptop w/
2. pre-installed R & RStudio (https://www.rstudio.com/products/rstudio/)
3. tidyverse package (https://www.tidyverse.org/)
4. gapminder dataset package (installation: https://cran.r-project.org/web/packages/gapminder/; about gapminder: https://www.gapminder.org/data/)

• Having trouble with installation & set-up? Ping us on Slack!

Useful Resources

1. Past DataViz workshop material from Oct 8 ‘18: https://bit.ly/rlel-gdrive-20181008
2. Relevant R (incl. tidyverse & ggplot2) & Slack cheatsheets: http://bit.ly/rlel-gdrive-cheatsheets
3. Hands-On Programming with R by G Grolemund (https://rstudio-education.github.io/hopr/) & R for Data Science by H Wickham & G Grolemund (https://r4ds.had.co.nz/)

• Start the discussion on Slack: https://rladies-eastlansing.slack.com OR http://bit.ly/rlel-joinslack-201811 (if you are a new member) #20181105-tidydata channel
  ** Not on Slack? Email us: eastlansing@rladies.org

💰Sponsor: Business Analytics, MSU (https://broad.msu.edu/)
Little Miss Tidyverse photo credit: Dani Navarro & Jen Richmond from R-Ladies Sydney!