For the final Open Lab of Spring 2019, Nuvan will be showing us linear regression and simulations. To get a head start, take a look at R For Data Science Chapter 22. We hope to see you there!
Welcome back! We hope you all enjoyed your spring break. For our next lab, Lorin will introduce us to working with loops and error handling in R. See you Thursday! These topics are covered in R For Data Science Chapter 21.
There will be no R Open Lab during the week of Spring Break. See you next week!
So far we’ve been doing a lot of data cleaning, transformation and analysis, but now it’s time to start taking a look at the different scripting techniques available in R. Tomorrow, Lorin will walk us through writing functions and using conditionals. Check out R for Data Science Chapter 19 to get a head start.
Today, Nuvan will guide you through working with text and categorical data while exploring strings and factors. This is also covered in R for Data Science Chapters 14 and 15.
Now that we’ve got some practice importing and cleaning data in R, it’s time to move on to the next step: analysis. This week, Lorin will show you how to use EDA techniques in R to discover patterns in your data. To get a head start, take a look at R for Data Science Chapter 7.
Do you ever wonder how we are able to present R code, plots, and formatted text all together on a single web page for our weekly lessons? The answer is R Markdown. This week, Nuvan will show you how to add some syntax to your code that can turn it into a professional looking report or website. As part of the process, we’ll also be reviewing material from weeks 1-3. R Markdown is covered in R For Data Science Chapter 27.
Tomorrow, Nuvan will guide us through some helpful methods for transforming data in R. Join us!
Today’s R Open Labs will introduce you to workflows and discuss why they are important. We’ll also be covering object, classes, ways to deal with missing data and more. See you soon!