How BBC data journalists use R for data visualization
Senior data journalists Clara Guibourg and Nassos Stylianou explain how the adoption of programming language R simplified graphics workflow at BBC News.
--
At the latest Hacks/Hackers London event, Clara Guibourg and Nassos Stylianou from the BBC Visual and Data Journalism team revealed how their team revamped its graphics workflow over the past year by developing bbplot — a customized version of the ggplot2 package — for R.
The package increased journalists’ productivity by giving more autonomy to the data team and freeing the graphics team from making the same charts over and over. As Guibourg explained: “Within the data team, we were using R for data analysis for quite a long time but, when it came to making charts, we had two options: if it was a quick turn-around thing, we made it ourselves, using the in-house chart tool, if we had more time, we would commission a chart from our designers.”
Last year, the data team started thinking that it was much better for their workflow to do everything in one place and to “go from the analysis step to the publication-ready chart, all within the same tool,” Guibourg said.
In March 2018 the ten members of the data team started experimenting by publishing the first BBC chart made from start to finish in R in March 2018. Since then, the team developed an R open source cookbook — which is a ready-made collection of instructions to configure something that everyone can copy or read to learn by example.
You can watch Guibourg and Stylianou’s full speech on our YouTube channel and read below for our main takeaways.
Why did the BBC choose R?
R is a statistical programming language used by many newsrooms for data analysis. If used in combination with the ggplot2 visualization package, the software can be used to show the distribution of large datasets and to turn it quickly into a chart.
“We found a lot of benefits with R. It gives you more freedom in terms of how you want your chart to look. Because we work with scripts now, everything is much more reproducible,” Guibourg said.
