R for Beginners

Please fill the pre-survey and evaluation to help us understand your expectations and thoughts about the workshops. 

• Pre-survey
• Workshop Evaluation Form

Thursday, January 20th, 2:00 - 4:00 PM

Content Covered

1. R and RStudio Installation

2. More about RStudio - interface, projects, working directory

3. R package installation

4. Objects, functions, and comments

5. Vectors and data types

6. Missing data

Details

Installation for PC

1. Download R from https://cran.r-project.org/bin/windows/base/
2. Download RStudio at https://www.rstudio.com/products/rstudio/download/#download

Installation for Mac

1. Check your version number and make sure to download the correct version of R/RStudio.

2. Download R from https://cran.r-project.org/bin/macosx/, and select the .pkg link based on your macOS version.

3. Download RStudio at https://www.rstudio.com/products/rstudio/download/#download

R & RStudio Installation Guidance

• https://rpubs.com/Earlien/guide-to-installing-R

Course Materials

• Before we Start
• Introduction to R

Additional Resources

• How to update R, remove R packages (https://www.linkedin.com/pulse/3-methods-update-r-rstudio-windows-mac-woratana-ngarmtrakulchol)

• Reproducible environment: https://rviews.rstudio.com/2019/04/22/reproducible-environments/ - how to safely upgrade packages, etc.

• Setup version control on RStudio: https://support.rstudio.com/hc/en-us/articles/200532077-Version-Control-with-Git-and-SVN

Recording

• Recording of Workshop 1 (Fall, 2021)
• Recording of Workshop 1 (Spring, 2022) 

Thursday, January 27th, 2:00 - 4:00 PM

Content Covered

1. Data frames and tibbles

2. Factors

3. Dates

Details

About the Dataset

The data used for this lesson are in the figshare repository at: https://figshare.com/articles/SAFI_Survey_Results/6262019

This lesson uses SAFI_clean.csv. The direct download link for this file is: https://ndownloader.figshare.com/files/11492171

Course Materials

• Starting with data

Extra Materials

• Factors

Recording

• Recording of Workshop 2 (Fall, 2021)

Thursday, February 3rd, 2:00 - 4:00 PM

Content Covered

1. Data wrangling with dplyr
2. Reformat data with tidyr
3. Export data

Details

Course Materials

• Data wrangling with dplyr & tidyr

Extra Materials

• RStudio cheatsheets

• Tidy data

Thursday, February 10th, 2:00 - 4:00 PM

Content Covered

1. About ggplot
2. Building your plots iteratively
3. Boxplots
4. Bar charts
5. Faceting

Details

Course Materials

• Data visualization with the package ggplot2

Extra Materials

• RStudio cheatsheets
• R Graph Gallery

Recording

• Recording of Workshop 3 (Fall, 2021)

R community

• Stack Overflow
• RStudio community
• Help for Tidyverse - a collection of R packages

Videos in O’Reilly database

• R programming for statistics and data science
• R programming
• Learn R Programming

Books

• R for Data Science
• R in action, 2nd edition
• Beginning data science in R: data analysis, visualization, and modeling for the data scientist
• Discovering Statistics Using R, by Andy Field, Jeremy Miles, and Zoe Field.
• Modern Statistics for Modern Biology by Susan Holmes & Wolfgang Huber.
• A Beginner's Guide to R by Alain Zuur, Elena Ieno, and Erik Meesters
• Data Manipulation with R by Philip Spector

• Jean Fan’s Style: http://jef.works/R-style-guide/
• Google R Style Guide: https://google.github.io/styleguide/Rguide.xml
• Tidyverse’s style: http://style.tidyverse.org/  
  • lintr package to automatically check for issues in styling your code (for tidyverse style guide)