R exercise: Analysing data

R exercise: Analysing data

While using R for your everyday calculations is so much more fun than using your smartphone, that’s not the (only) reason we’re here. So let’s move on to the real thing: How to make data tell us a story.

First you’ll need some data. You haven’t learned how to get and clean data, yet. We’ll get to that later. For now you can practice on this data set. The data journalists at Berliner Morgenpost used it to take a closer look at refugees in Germany and kindly put the clean data set online. You can also play around with your own set of data. Feel free to look for something entertaining on the internet – or in hidden corners of your hard drive. Remember to save your data in your working directory to save yourself some unneccessary typing.

R crash course: Workspace, packages and data import

by Kira Schacht 3 Comments
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

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.

Working with vectors

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.

You can install R here. Since it is open source, there are tons of packages with additional functions and possibilities. We will show you how to find and install them in the next chapters.