Tag: tidytuesday

David Robinson’s R Programming Screencasts

David Robinson’s R Programming Screencasts

David Robinson (aka drob) is one of the best known R programmers.

Since a couple of years David has been sharing his knowledge through streaming screencasts of him programming. It’s basically part of R’s #tidytuesday movement.

Alex Cookson decided to do us all a favor and annotate all these screencasts into a nice overview.


Here you can search for video material of David using a specific function or method. There are already over a thousand linked fragments!

Very useful if you want to learn how to visualize data using ggplot2 or plotly, how to work with factors in forcats, or how to tidy data using tidyr and dplyr.

For instance, you could search for specific R functions and packages you want to learn about:

Thanks David for sharing your knowledge, and thanks Alex for maintaining this overview!

Creating plots with custom icons for data points

Creating plots with custom icons for data points

Data visualizations that make smart use of icons have a way of conveying information that sticks. Dataviz professionals like Moritz Stefaner know this and use the practice in their daily work.

A recent #tidytuesday entry by Georgios Karamanis demonstrates how easy it is to integrate visual icons in your data figures when you write code in R. You can simply store the URL location of an icon as a data column, and map it to an aesthetic using the ggplot2::geom_image function.

Do have a closer look at Georgios’ github repository for week 21 of tidytuesday. You will probably have to alter the code a bit to get it to work. though!

For those who haven’t moved away from base R plotting functions yet, here’s a good StackOverflow item showing how to use icons in both base R and tidyverse.

Now that I think of it, the above probably uses the same methods that were used to make this amazing Game of Thrones map in R.

rstudio::conf 2019 summary

rstudio::conf 2019 summary

Cool intro video!
Thanks to Amelia for pointing to it

Welcome to rstudio::conf 2019

Similar to last year, I was not able to attend rstudio::conf 2019.

Fortunately, so much of the conference is shared on Twitter and media outlets that I still felt included. Here are some things that I liked and learned from, despite the Austin-Tilburg distance.

All presentations are streamed

One great thing about rstudio::conf is that all presentations are streamed and later posted on the RStudio website.

Of what I’ve already reviewed, I really liked Jenny Bryan’s presentation on lazy evaluation, Max Kuhn’s presentation on parsnip, and teaching data science with puzzles by Irene Steves. Also, the gt package is a serious power tool! And I was already a gganimate fanboy, as you know from here and here.

One of the insights shared in Jenny Bryan’s talk that can be a life-saver

I think I’m going to watch all talks over the coming weekends!

Slides & Extra Materials

There’s an official rstudio-conf repository on Github hosting many materials in an orderly fashion.

Karl Broman made his own awesome GitHub repository with links to the videos, the slides, and all kinds of extra resources.

Karl’s handy github repo of rstudio::conf

All takeaways in a handy #rstudioconf Shiny app

Garrick Aden-Buie made a fabulous Shiny app that allows you to review all #rstudioconf tweets during and since the conference. It even includes some random statistics about the tweets, and a page with all the shared media.

Some random takeaways

Via this tweet about this rstudio::conf presentation
Some words of wisdom by Emily Robinson (whom we know from here)
You should consider joining #tidytuesday!

Extra: Online RStudio Webinars

Did you know that RStudio also posts all the webinars they host? There really are some hidden pearls among them. For instance, this presentation by Nathan Stephens on rendering rmarkdown to powerpoint will save me tons of work, and those new to broom will also be astonished by this webinar by Alex Hayes.