Online R Challenge

Using the R programming language can be a great tool in a variety of disciplines for data analysis and visualization. To help you get started, we’ve compiled several video tutorials, a list of resources and a space to chat about what you’re doing in R. Check out our page and join the conversation!

Getting started with R

Learn how to install R and RStudio in this tutorial with Elizabeth E. Esterly, a graduate student in computer science at the University of New Mexico.

Setting up your RStudio workspace

Learn your way around the RStudio environment and how to get it set up and ready to handle some serious data in this tutorial with Elizabeth E. Esterly, a graduate student in computer science at the University of New Mexico.

We have two workshops coming up!

Join us Oct. 23 and Dec. 4 for in person workshops on R. Register here and here. We encourage you to attend both events and to have R Studio on your computer a head of time.

We also offer weekly office hours.

Stop by the Advance at UNM space from 11 to 2 on Thursdays to have computer science grad student Elizabeth E. Esterly answer your questions.

 

Copy of AdvancePanels

HELPFUL RESOURCES

 

Here are our top picks for you about using R.

Click here first for R language information and then here to download it.
 
 
And learn about data visualizations in R here.
 
Online R Challenge

Join our conversation

We’re here to chat about your work with data and R. Each week, we’ll ask a different question or address a new part of R. You can ask your questions too! UNM computer science graduate student Elizabeth E. Esterly will address your comments below.

Week of Oct. 9: What’s the story you want your data to tell?

 

Leave your thoughts in the comment section.

4 Comments

  1. Justin
    October 6, 2017 @ 9:14 am

    Hello, I was wondering R can work with very large .csv files, say in the multiple GB range, or if there are any tricks to handling them.

    Reply

    • advance
      October 8, 2017 @ 11:41 am

      Yes! R can work with large .csv files–up to about 10 GB, or the size of your computer’s memory (RAM), whichever is smaller. (For files larger than this, you’ll need to use specialized software like Hadoop.) But loading such a large dataset can be quite slow. To speed up the process, you can try using the fread function from the data.table package; more info can be found in the official R documentation here.
      I hope this helped!
      –E.

      Reply

  2. Sarah
    October 8, 2017 @ 1:11 pm

    I was wondering if R would be good for plotting or can it just do statistical analysis?

    Reply

    • advance
      October 9, 2017 @ 7:55 pm

      You can do some beautiful plots in R–check out the link we posted above on data visualization for an example. You can get the most out of R plotting by using the free ggplot2 library, which is part of a group of libraries called the Tidyverse. But R is strong for basic plotting with its built-in functions as well. For some hands-on instruction on how to get started with plotting in R, I’d encourage you to join our workshop series. Thanks for your question!
      –E.

      Reply

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