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This is the repo for the two-day short course, "Introduction to R & RStudio" given at rstudio::conf(2018) January 31 and February 1, 2018.

Description: This is a two-day hands on workshop designed for people who are brand new to R & RStudio and who learn best in person. You will learn the basics of R and data science, and practice using the RStudio IDE (integrated development environment) and R Notebooks. We will have a team of TAs on hand to show you the ropes, and help you out when you get stuck.

These materials were based on Introduction to R (2014), and https://github.com/rstudio/master-the-tidyverse (2017). They are intended to be appropriate for people who have never used R before.

To download the materials, click on "Clone or download" and select "Download ZIP"

The materials are also available as two separate RStudio Cloud projects:

• Day 1
• Day 2

Both day1 and day2 include folders of code, slides, cheatsheets, and (on day 2) data. Files should be consistently named so you can see the correspondence. For example, 02-Visualization.pdf corresponds with 02-Visualization.Rmd and 02-Visualization-Solutions.Rmd

Day 1

• 01-Introduction (what is R, what is RStudio)
• 02-Visualization (visualizing data using ggplot2)
• 03-DataTypes (vectors, matrices, data frames, vector types, coercion)
• 04-Syntax (selecting rows and columns using base R and dplyr-- compare/contrast)

Day 2

• 06-Import (importing data using base R and readr-- compare/contrast)
• 07-BestPractices (cleaning up your workspace, ideas for organization, things to read)
• 08-Transform (more dplyr, making many-to-few and many-to-many transformations, joining data)
• 09-Tidy (skipped in the workshop, covers tidying data using gather() and spread())
• 10-Model (linear modeling, broom, logistic regression)
• 11-GoingForward (installing R and RStudio locally, learning more and getting help)

Amelia McNamara

• [email protected]
• http://www.science.smith.edu/~amcnamara/
• @AmeliaMN

Intro to R & RStudio by Amelia McNamara is licensed under a Creative Commons Attribution 4.0 International License. Based on Introduction to R (2014), and https://github.com/rstudio/master-the-tidyverse (2017).