It’s a cliche, but that doesn’t make it less true: practice makes perfect. Last May I discovered a great way to practice my data visualisation skills in R: Tidy Tuesday. The R for Data Science online learning community (R4DS) posts a new data set every week. Make your plots based on the data, and share them on Twitter along with the code and the hashtag #TidyTuesday – everyone can join! Here are ten reasons why Tidy Tuesday is my favourite day of the week.
1. Getting inspired by the creativity of others
I always love to see the variety of plots coming from the same data set. Occasionally, I see a Tidy Tuesday plot and I think: “That’s a great idea, I wish I thought of it myself!”. Fortunately, I can look at the code to see how the plot was made. This is an easy way to learn cool new tricks from others.
Tidy Tuesday is perfect for exploring new packages. Through Tidy Tuesday I learned about the gganimate package to make animated GIFs. This can be helpful when you want to show a trend over time. Another package I first used for Tidy Tuesday is ggrepel. This package adds labels to data points, making sure that the labels do not overlap any points or other labels.
3. Learning to make plots self-explanatory
What message do I want the graph to convey? Every week, I challenge myself to make my #TidyTuesday plot as clear as possible. My goal is to make a stand-alone image that can be understood without additional information. I try to focus on one message at the time, this is often more effective than trying to say it all with one plot. Labels, colors, titles and subtitles can be used to draw attention to specific parts of the plot.
Tidy Tuesday was set up to provide hands-on experience with the tidyverse. The tidyverse is a consistent set of R packages, with dplyr and ggplot2 being the most notable. The tidy way of doing things was new to me, and Tidy Tuesday has been very useful to work on my tidyverse skills.
5. Learning to fine-tune graphs
Ggplot2 is the graphics package of the tidyverse. Almost everything can be adjusted in a ggplot graph, which is great. You can change text font, size, position, and alignment. You can change the position and appearance of the legend, and much more. If you use color in the graph itself, there are many color palettes to choose from. I often use Brewer colors and the viridis color scheme. Having control over these details means you can make your plot more powerful.
6. Discovering new data every week
I can be a bit of a perfectionist when it comes to data analysis and graphs. A good thing is that Tidy Tuesday is a weekly event. This taught me that putting something out there is more important than sitting on it endlessly and trying to make it perfect. Having a busy week? You can always take a break and jump in again next week. New data is usually posted on Monday or early Tuesday morning. Despite the name, you don’t have to limit yourself to Tuesdays. Any day is perfect to post your #TidyTuesday graph!
7. Being part of the #rstats Twitter community
The community is friendly to beginners. If you mention you are participating in Tidy Tuesday for the first time, you will most likely get a warm welcome. I love to see first-time participants contributing to the community. You can always ask for feedback on your plot and get some useful suggestions.
Tidy Tuesday data sets have covered fast-food calories, airline safety, alcohol consumption, pets, and comic characters, to name a few. If you are looking for a data set to explore and practice with, you can pick one from the list of previous data sets.
There are so many types of graphs – line graphs, bar graphs, box plots, violin plots, heat maps, dot plots… The R graph gallery gives a nice overview of the many different visualisation types. Not all types will be suitable for a certain data set. However, with the variety of Tidy Tuesday data you will eventually get to try pretty much all graph types.
Not only R and tidyverse enthusiasts post under the #TidyTuesday hashtag. Tuesday is also a perfect day to tidy up your home. I find it amusing to come across cleaning tips when I’m browsing through Tidy Tuesday plots. These “other” Tidy Tuesday posts might even inspire you to start cleaning after you posted your plot!
If you want to join the fun, go to the Tidy Tuesday GitHub page to read more and get this week’s data. If you are already participating in Tidy Tuesday, I’m curious: what do you like about it? What have you learned? Let me know by leaving a comment!