As you know by now, R is all about functions. In the event that there isn’t one for the exact thing you want to do, you can even write your own! Writing your own functions is a very useful way to automate your work. Once defined, it’s easy to call new functions as often as you need. It’s a good habit to get into when programming with R — and with lots of other languages as well.
R exercise: Analysing data
R crash course: Workspace, packages and data import
In this crash course section, we’ll talk about importing all sorts of data into R and installing fancy new packages. Also, we’ll learn to know our way around the workspace.
Your workspace in R is like the desk you work at. It’s where all the data, defined variables and other objects you’re currently working with are stored. Like with a desk, you might want to clean it every once in a while and throw out stuff you don’t need any more. There’s a few useful commands to help you do that. Take a look and try them out:
R crash course: Vectors
Now that you installed RStudio, learned about assignments and wrote some basic code, there’s nothing stopping you from becoming a journocoder!
To get a deeper understanding of how R stores your data, we’re now going to take a closer look at data structures in R, starting with a central concept: Vectors.
R crash course: Your first code
R crash course: Getting started
At journocode, we’re starting out with an intro to the tool we rely on most right now: The statistical programming language R. “R: A Language for Data Analysis and Graphics” is mostly used in statistics, but is very useful for journalists working with data as well.
On the way to @nrecherche Daten-Labor @ TU Dortmund. Doing #rstats – what else? #ddj #rddj pic.twitter.com/D1GvWbIwmT
— Timo Grossenbacher (@grssnbchr) 22. Oktober 2015