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Articles

Welcome to my blog! Its original title, “pars pas les mains vides!” which translates as “don’t leave empty-handed!”, conveys what I’m aiming to do: capture things I’ve picked up along the way in the weird and wonderful worlds of #rstats, data science and dataviz, and share them with others who may find them useful for their own adventures.

Feel free to pinch the best bits and reuse them for your own purposes - that’s what these articles are here for! And if you want to say thanks or hello, get in touch!

Optimising the use of colours for storytelling in a spaghetti plot

Data visualisation

Data storytelling

One of my clients recently asked me for tips on optimising spaghetti plots. Those plots with multiple trend lines all superimposed on top of one another, where it can often be very difficult to figure out what is what… They are an important part of the dataviz vocabulary in his field, so the mission was to figure out how to make the most of them!

More than pretty graphs: Tips, tricks and resources to elevate your dataviz

Dataviz

Data Storytelling

A 45-minute tool-agnostic dataviz workshop, exploring how we can make the most of data visualisations to tell compelling stories with context

Level up your plots - Shiny in Production 2024 Edition

Dataviz

Data Storytelling

A 3-hour in person code-along workshop, exploring how we can make the most of colours, text, styling annotations, and interactivity to create compelling data visualisations

Ah, Ha, Ha, Ha, Parameterise!

Dataviz

Coding tips

Parameterise

RMedicine 2024 talk where I create and refine a parameterised plot function, with an exploration of how this approach can contribute to flexible and reproducible data-to-viz workflows across the team.

Ready, Steady, Viz! Tips, tricks and no-code resources for stand-out data visualisations

Dataviz

Data Storytelling

Inaugural talk on for the Black in Psych 2024 Summer Series | 12 resources, and many tips besides for creating compelling and memorable visualisations

From alright to all ready to publish

Dataviz

Coding tips

Advanced dataviz talk for RGlasgow, exploring how we can visualise rainfall in Glasgow and Edinburgh

Ah, ha, ha, ha, Parameterise!

Dataviz

Parameterised plot

Coding tips

A workshop on creating parameterised plot functions, which allowed us to create plots with different data, different variables, and different styling, all from one function.

Parameterising a multi-part plot

Data visualisation

Parameterised plots

Today’s #rstats exercise in building parameterised plots is brought to you by my desire to avoid copy-pasting and making minor edits to 200+ lines of code in order to create two variants of a set of interactive graphs for a client. I decided to blog my way through the process to highlight a few tips and tricks I’ve picked up along the way.

“So much more than pretty graphs”: Recent adventures in automating dataviz solutions

The Data Lab Community - Women in Data and AI Meetup | I talked about dataviz design systems, parameterised plots and WebR, before enjoying a talk by Martina Pugliese, and joining her for a fireside chat with Ally Orr, to discuss how we ended up here and what we’re excited about.

A quick experiment with WebR: how much can I do in under an hour?

dataviz

formatting

numbers

I got a leaflet through my door the other day with a bar graph that just didn’t look right. It inspired me to create a tool to easily create a bar graph online, so that people can do a quick side-by-side comparison. I’ve been wanting an excuse to give WebR a go, and this seems like a good place to start, so I thought I’d live blog my way through my first hour of playing with WebR. Ready, get set, go!

Formatting numbers for easy readability in R

dataviz

formatting

numbers

Sometimes you want a raw number. Other times, you want a number that you can instantly verbalise. This post explores an easy solution for getting from “1234567890” to “1,234.6M” without installing any additional packages.

Getting fonts to work in R

dataviz

typography

how-to

Getting fonts to work in R and RStudio can be tricky! This post walks through the different steps we need to follow to give ourselves the best chance of success.