From the @DSLC
βchives:
Mastering Shiny: Graphics https://youtu.be/7cc9V2MDY-w #RStats
Python for Data Analysis: Data Analysis Examples https://youtu.be/LxtCdtCbhmE #PyData
The #TidyTuesday Cookbook: Lemurs: manipulating images in R https://youtu.be/J7Yez2NC0NY #DataViz #RStats #ggplot2 #dataVisualization
Advanced R: (OOP) Trade-offs https://youtu.be/vEButxFIvLw #RStats
Support the Data Science Learning Community at https://patreon.com/DSLC

Some of the things we covered:
π How to write a function to re-use your #ggplot2 charts across multiple datasets
β How to create a parameterised report in #Quarto
π οΈ How to generate many reports across different parameter sets
π How to show and hide report content based on output format and parameter values
π How to generate multiple similar sections within one report, mapping across variables
Recent @DSLC club meetings:
The Art of Data Visualization with ggplot2: The #TidyTuesday Cookbook: Lemurs: manipulating images in R https://youtu.be/J7Yez2NC0NY #RStats #DataViz #ggplot2
From the @DSLC
βchives:
Advanced R: Subsetting https://youtu.be/qtUgKhw39Yo #RStats
Outstanding User Interfaces with Shiny: Web application concepts https://youtu.be/dB1zRW9r_Bw #rshiny #RStats
Support the Data Science Learning Community at https://patreon.com/DSLC

An annotation-heavy, faceted area chart for #TidyTuesday this week providing different ways of looking at historic ship production in Italy π’
π Made in #RStats with #ggplot2
Code: https://github.com/nrennie/tidytuesday/blob/main/2026/2026-05-05