Welcome! This workshop will provide an introduction to the basics of data analysis in R (including loading and writing excel and other common file formats, basic analysis, and tidyverse methods), and will also explore data visualization using ggplot, and task automation through the cronR (mac) and taskscheduleR (windows) packages. If time permits or in a follow-up workshop, we can also explore selections from topics such as mapping and geocoding in R, connecting to databases in R, using API’s to pull data automatically in R (e.g. from data.cdc.gov), and working with census data in R.
Instructors: Marisa Eisenberg, Michael Hayashi, and Julie (Jules) Gilbert (University of Michigan, Ann Arbor)
Below is an overview of the topics we’ll cover (and when!) so you can join for the parts of the workshop that make sense for you. Feel free to listen in even if you’re already familiar with a topic (or you are worried you may not have the skills for one) —in either case we hope it will help give you some context and hopefully you’ll find some useful info!
We’ve given estimated times for each topic below, but note they may be somewhat approximate! We may adjust as needed based on how comfortable everyone is working with R.
You should have received an email already with this info! But if for some reason you haven’t already installed the R, RStudio, and the packages we’ll be using today, here are the instructions and the installation check code that you can run to make sure you’re all set!
If you need help at any point during the workshop, you can join this zoom room:
And Jules will be available to help you get sorted out!
Before we start, please download this zip file of all the datasets we will use for this workshop. Put it in whatever folder/directory you plan to put all your workshop code in and then unzip it. You should have a folder called “datasets” with a bunch of csv and excel data inside!
1-1:10pm (10 minutes)
Covers: basic use of R, RStudio (the environment, console, etc.), loading packages (basically making sure everyone is set up and ready to go!)
1:10-1:30pm (20 minutes)
Covers: dataframes, loading csv and excel data, basic operations with dataframes
1:30-1:50pm (20 minutes)
dplyr: the pipe operator!
1:50-2:10pm (20 minutes)
2:10-2:30pm (20 minutes)
2:30-2:50pm (20 minutes)
2:50-3:00pm (10 minutes)
flexdashboard), basics of building websites
More to be added soon!
All the [R package cheatsheets](https://github.com/rstudio/cheatsheets/blob/main/data-visualization.pdf! A super handy resource