Investigating Data with R
So you’ve got the fundamentals of data journalism down. You’re interrogating spreadsheets like a pro and able to use pivot tables like the data Swiss-army-knives they are.
But sooner or later you know you’ll come up against a dataset so big it’s going to crash Excel if you even try to open it. Or your questions are becoming too complex for Excel’s built-in analytics tools to handle. Maybe you find yourself frequently updating a dataset or running the same calculations for your reporting. Or you just want to automate some of the collection or visualisation of a dataset you keep having to do.
Then R is your friend! And this is your opportunity to get to know it better.
Invest in learning how to leverage the potential of the R programming language and it will repay you many times over. As well as reclaiming precious research time from repetitive tasks, you’ll make the first steps into using code for journalism and give yourself an edge, whether in the job market or in nailing the evidence you need to stand up that impactful story. What’s more, this is an investment you can cash in on straight away, taking back skills you can apply to your work instantly.
Our expert trainers will take you through how to simplify the tasks you’re familiar with, automate the tasks you’re bored with and open up new areas for investigation you weren’t aware of.
Want to know more about how R can help with data-driven journalism? This piece by Carmen Aguilar-Garcia, Data Journalist with Sky News and regular at CIJ Training Courses explains why and how coding has helped her to keep on top of a huge and quickly developing story like the Covid19 pandemic.
Group size: max 10 people
Class duration: 1.5hrs x 3 days
Level of participation: high. Hands-on, screenshares, regular Q&As, required self-directed study
The course is taught online to get you started, but you receive a workbook to take you through the concepts and coding steps you need to learn. After the first three online sessions, you will use the workbook at your own pace. It includes advice on getting further tuition and practice, for free, online. As with our data courses, you can stay in touch with the trainer after the course when you get stuck and need help.
This course will need you to have the following software/apps/tools on your computer:
Please go to https://rstudio.cloud/ ahead of the start of the course and create a new account. Ignore any requests for payment, all the content in the class will work with a free account. By the end of the course, you will be able to decide whether you wish to continue using R and Rstudio, and the trainer will explain how best to do this.
One of the following recommended browsers:
- Mozilla Firefox
- Google Chrome
Camera and audio
This course will be hosted on Zoom. To find out more about how we use Zoom, please check out our Zoom InfoSec page.
Course objectives: by the end of the course you will have learned the basics of using R and its most popular interface RStudio. You will know how to explore your data and do the common analysis tasks. You will learn to do your first visualisation of your data using the most popular R package ggplot2. (The whole course is based on the suite of packages called the Tidyverse, of which ggplot2 is one part.)
- 15 March 2021 10.00–11.30 Time zone: GMT
- 17 March 2021 10.00–11.30 Time zone: GMT
- 19 March 2021 10.00–11.30 Time zone: GMT
In line with our non-profit mission, our pricing operates on a sliding scale, ensuring large organisations pay more to subsidise places for smaller newsrooms, freelancers and students.
*Students places for this course are capped, due to limited capacity. Anyone registering as a student will be asked for a photo/scan of their student ID ahead of the course.
**Employed individuals who cannot have their employers pay for the course are entitled to the freelancer rate. Note that we are a small charity and rely on your honesty so please do not register as a freelancer if your employer is reimbursing you for the course.
We have a strict policy of No Refund and No Transfer of bookings.