Posts

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.

This is a mix of blog posts, “tweetorials” and LinkedIn posts I wrote as I was discovering fun things, and talks. It’s fully searchable through the search function in the nav bar.

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 hello, get in touch!

Make it your own - Tips and tricks for stand-out dataviz with R and ggplot2

data-visualisation

r-how-to

parameterised-plots

dataviz-design-system

Lunchtime workshop for the Manchester Uni useR group, looking at making the most of ggplot2 (including a fun new feature!) for clear, engaging data visualisations which always look like your own.

RiskyViz - Dataviz tips, tricks and traps to avoid when parameterising graphs about risk

data-visualisation

r-how-to

parameterised-plots

Lightening talk for the inaugural R Consortium R!SK Conference 2026. This talk explores dataviz design principles and their implementation within ggplot, along with important safety features we can build in, to maximise the impact and reliability of our visuals in communicating risk.

Beautifully reproducible: (mis)adventures in automating data-to-viz pipelines

data-visualisation

r-how-to

parameterised-plots

Keynote talk for the NHS-OA 2025 conference, in which I explore different steps we can take to make our dataviz functions cope with whatever data we throw at them, and to approach R and package updates with confidence - dataviz tests!

Creating compelling visualisations in R with ggplot2

r-how-to

data-visualisation

storytelling

annotations

ggplot2

A code-along workshop for AFBI, exploring principles of dataviz design and applying them using ggplot2 and a few extra packages

On-brand accessible dataviz

data-visualisation

r-how-to

dataviz-design-system

My contribution to the RSS panel on Accessibility at the 2025 RSS Conference in Edinburgh.

Here’s one last #unpluggedViz from the summer holidays

data-visualisation

data-art

misc

First day back at work after a much needed break. Here’s one last #unpluggedViz from the summer holidays before I resume normal service of posting coding solutions to interesting dataviz challenges.

Every day a school day when creating custom R packages!

misc

Today, I’m making maps and a documentation how-to about maps, because… the client makes maps and needs to see how to apply the colours we’ve created to them! Tomorrow, it will be a swimmer plot for a different client.

Visualise, Optimise, Parameterise! New code-along workshop video

data-visualisation

ggplot2

parameterised-plots

In the workshop, we worked through the traps I’ve typically encountered in creating these parameterised plotting functions, and how to avoid them. There was even one that came up in the workshop preparation!

Yesterday’s #unpluggedViz was a collaborative effort between me and dad

data-visualisation

data-art

Mapping out what we hear when a train leaves / arrives at a métro station.

Yesterday’s #unpluggedViz reflecting on its own Yesterday (the race!)

data-visualisation

data-art

… and a comparison with running the same distance 10 years ago. Pretty chuffed!

Today’s #unpluggedViz. A calendar check just in time.

data-visualisation

data-art

I did chuckle when I picked up my race number!

A dataviz re-do from the Nordic Society of Human Genetics and Precision Medicine conference

data-visualisation

annotations

One of the highlights of preparing workshops for different groups is that I get to have a go at reworking plots that are relevant to them, to see how the principles we’re discussing could work on real dataviz challenges they face.

Picking semantic colours, then making them accessible and on-brand

data-visualisation

r-how-to

The other thing we talked about in Monday’s workshop was how to pick a semantically-meaningful colour that’s also on brand, when your brand guidelines don’t include that colour.

Today’s #unpluggedViz, reflecting on the quarter that has just ended

data-visualisation

data-art

misc

A helpful excercise in advance of tomorrow’s board meeting. It’s been a bit mad, and we can clearly see why I needed to take on a project manager!

In-house dataviz workshop for the British Heart Foundation

data-visualisation

This morning, I joined the analysts from the British Heart Foundation online for a dataviz workshop. I set up a silly mission: let’s imagine that the BHF is hosting the next Great British Bake Off…

Two #unpluggedViz contributions from the weekend

data-visualisation

data-art

misc

You win some, you lose some!

Today’s slightly mad idea: how about an ad hoc hashtagunpluggedViz club this summer?

data-visualisation

data-art

misc

“With the holidays now in full swing, I know I’ll benefit from some kind of structure to help me embrace the change of pace and enjoy reflecting on the things we get up to in the summer juggle.”

An aside about running a business

misc

I tend to not talk much about the business side of things on here, but there was a beautiful ‘wait, and you’re also a mum?’ moment at a recent conference.This led to a few questions about what it’s like to start your own consultancy business.

Today’s visualisation challenge

data-visualisation

parameterised-plots

How many people picked each of 12 possible options as the top, second top and third top priority, and how can we make sure this scales nicely for 100+ respondents…

It’s #ggplot2’s 18th birthday

data-visualisation

ggplot2

“A perfect excuse to recirculate this plot I made entirely with #ggplot2 that looks like a cake!”

Visualise, Optimise, Parameterise!

data-visualisation

r-how-to

parameterised-plots

annotations

The penguins are back! And this time, it’s for a Beak-Off. They are organising themselves into teams to see which team can show off the biggest range of beak lengths. Retrace our steps in this code-along workshop where we built a graph, made it better (and interactive!), and optimised the parameterised plotting function to address all the judges’ requirements.

Reworking a standard graph into something more intuitive

data-visualisation

storytelling

“That’s a wrap for the #dataviz workshop sessions I’ve been leading yesterday and today for NSHG-PM’s 2025 conference in Copenhagen.”

An interdisciplinary journey in data visualisation

data-visualisation

storytelling

Keynote talk at the Women in Data Science 2025 conference held at Heriot Watt University. An exploration of how I have ended up doing what I do, peppered with tips and resources for future dataviz projects.

Fixing awkward backgrounds in ggplot2

r-how-to

ggplot2

When creating graphs and maps with a fixed coordinate system (e.g. coord_sf() or coord_polar()), the background colour can end up not covering the entire export area. There are a few different ways of fixing the issue - one of which I think is more elegant than the others, involving a simple function which makes use of {cowplot}.

Optimising the use of colours for storytelling in a spaghetti plot

data-visualisation

storytelling

ggplot2

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

data-visualisation

storytelling

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

Leveraging Shiny for creating high-end bespoke parameterised plots (without learning how to code)

parameterised-plots

data-visualisation

ggplot2

A behind-the-scenes look at an app I developed to allow a client who doesn’t code to create parameterised visualisations straight from his data.

Level up your plots - Shiny in Production 2024 Edition

r-how-to

data-visualisation

storytelling

annotations

ggplot2

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

Dataviz in the wild

data-visualisation

Working away from home this week I spotted this dataviz in the wild as a fun example of how to get round the fact that you only have one colour to play with.

Ah, Ha, Ha, Ha, Parameterise!

data-visualisation

r-how-to

parameterised-plots

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.

The joy of seeing another dataviz design system come together!

data-visualisation

dataviz-design-system

This is such a satisfying milestone in a project, when the dataviz design system comes together and I get to show the client what it looks like with demo plots.

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

data-visualisation

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

data-visualisation

dataviz-design-system

annotations

r-how-to

ggplot2

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

Ah, ha, ha, ha, Parameterise!

data-visualisation

parameterised-plots

r-how-to

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

r-how-to

ggplot2

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

data-visualisation

dataviz-design-system

storytelling

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?

data-visualisation

annotations

r-how-to

ggplot2

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

data-visualisation

annotations

r-how-to

ggplot2

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

data-visualisation

annotations

r-how-to

ggplot2

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.

It’s been an epic year! I feel very privileged to do what I do.

misc

Pssst! I’m not on Twitter (X) much any more, but I’m posting the same type of content over on LinkedIn where a good number of us have found our feet.

Ten tips for better text: Typography meets ggplot and friends

data-visualisation

r-how-to

annotations

RLadies Rome | A code-along workshop

Dynamic annotations: 10 tips for better text

data-visualisation

r-how-to

annotations

storytelling

Shiny in Production 2023 Keynote | Ten tips for better text in dataviz, using data from the Great British Bake Off

So much more than pretty graphs: The value of creating and implementing a dataviz design system in R

data-visualisation

ggplot2

dataviz-design-system

NHS-R 2023 Conference | Online talk

Level Up Your Plots: Using colour, annotations, text hiearchy and other tricks to make your data story stand out

data-visualisation

ggplot2

r-how-to

annotations

storytelling

NHS-R 2023 Conference | Online code-along workshop

Building a Dataviz Design System for a Medical Research Project

dataviz-design-system

data-visualisation

RMedicine 2023 | Lightening talk

Level up your plots: Using colour, text hierarchy and annotations to create compelling and memorable data visualisations

r-how-to

ggplot2

annotations

data-visualisation

RMedicine 2023 | A code-along workshop

R-Ladies Edinburgh | Level up your plots

data-visualisation

r-how-to

annotations

dataviz-design-system

ggplot2

An in-person code along workshop exploring how to make good use of colour and text hierarchy in our plots and their annotations

Using colour and annotations for effective storytelling

data-visualisation

storytelling

annotations

ggplot2

r-how-to

Workshops for Ukraine | A 2-hour code-along workshop

Beautifully Annotated: Enhancing your ggplots with Text

data-visualisation

r-how-to

annotations

parameterised-plots

R-Ladies Cambridge | Inaugural lunchtime dataviz meetup

Dates in R, the easy way

r-how-to

annotations

data-visualisation

Today’s #rstats “this was easier than I thought” moment: zoo::as.yearmon()

This week’s #TidyTuesday: ‘lesser spotted’ birds

data-visualisation

ggplot2

r-how-to

I had wanted to add one of these plots to my portfolio for a while!

One solution to make text stand out against most backgrounds

data-visualisation

r-how-to

ggplot2

Creating a #dataviz with smallish text, varying colours, programmatic text alignments, and you want the text to look crisp and easy to read regardless of its background? Using #rstats and #ggplot? ggfx::with_outer_glow() is your friend!

Adding a function which detects the client’s OS and silently loads fonts accordingly

r-how-to

dataviz-design-system

annotations

Using custom fonts in #rstats can be tricky, specially if the fonts need to use a variant on the standard family (e.g. Medium) which can be called different things across Windows and Mac.

Two rstats dataviz aha moments from this morning

data-visualisation

ggplot2

r-how-to

#1: 🧇 ordering the fill colour when using waffle::geom_waffle(), and #2: 🐮 getting rid of white space around a plot with fixed coords (such as, for example, a waffle plot)

My talks from the NHS-R conference

dataviz-design-system

data-visualisation

ggplot2

r-how-to

I really enjoyed the opportunity to speak to a live audience again after so long - and it was such a lovely conference as a first one back! So impressed by all that is going on with #rstats within the #NHS!

Still my favourite form of dataviz

data-visualisation

misc

Scores in the handwriting of their composers, a musical card game and an early comic of sorts in Sheare’s Bible.

Palatable Palettes: Five tips for creating and applying bespoke colour schemes

data-visualisation

ggplot2

storytelling

dataviz-design-system

NHS-R Community Conference | Five tips for making good use of colours in your ggplots

Variations on a ggtheme: Applying a unifying aesthetic to your plots

data-visualisation

dataviz-design-system

r-how-to

NHS-R Community Conference | Three reasons why you should apply a bespoke ggplot theme to your plots & how to do that

Replacing NAs in a dataframe

r-how-to

Today’s #rstats “I wish I’d known this sooner” moment: tidyr::replace_na()

Take a string and return a nicely formatted quote

r-how-to

data-visualisation

ggplot2

annotations

This morning I’ve been building an #rstats function to take a string and return a nicely formatted quote, using a client’s brand guidelines. It’s been a fun adventure involving fonts, hacking geom_textbox() and allowing for different string lengths.

Level Up Your Plots: A Code-along Workshop

data-visualisation

ggplot2

r-how-to

storytelling

Online Workshop @ NHS-R 2022 Conference - November, 2022

Recreating one of Janusz’s iconic drip cakes using data from the #GBBO

data-visualisation

ggplot2

data-art

For this week’s #TidyTuesday Technical Challenge, I decided to recreate one of januszbakes’s iconic drip cakes using data from the #GBBO.

Setting up fonts on RStudio Cloud

data-visualisation

r-how-to

annotations

Today I’ve been exploring RStudio Cloud in preparation for an #rstats #dataviz workshop , and I’m really impressed with how easy it is to use!

🚨 New #rstats package: verbaliseR

r-how-to

annotations

A bundle of functions that help turn #rstats output into human-looking sentences, with the fun quirks of the English language.

Crafting a data-driven fundraising campaign

data-visualisation

storytelling

annotations

Breaking down the process involved in creating a data-driven fundraising campaign for Origin Scotland.

I made it onto the Information is Beautiful long list 🥳

data-visualisation

data-art

storytelling

ggplot2

Delighted to share that both of my entries made it onto the long list for the Information is Beautiful awards - along with over 1000 others!

Custom fonts in Quarto slides published via GitHub pages

r-how-to

storytelling

I spent a good chunk of yesterday doing battle with a custom font that I needed to import from a directory rather than from Google Fonts into a #quartoPub presentation.

Level Up Your Plots: Enhance the story telling capabilities of your datavisualisations

RUG @ HDSI - September, 2022

data-visualisation

annotations

parameterised-plots

r-how-to

storytelling

It was an absolute pleasure discussing these design tips and coding tricks with the Harvard Data Science Initiative R User group. I particularly enjoyed the Q&A at the end…

rstats package update

r-how-to

data-visualisation

ggplot2

{monochromeR} now generates a ggplot object, which you can easily feed to useful tools like colorblindr::cvd_grid() to check the accessibility consequences of your colour choices. Here’s a quick demo, and a surprise.

Looking to highlight specific lines in your code chunks in Quarto?

r-how-to

Don’t forget to set echo to true!

Automating sentences with R

annotations

data-visualisation

r-how-to

parameterised-plots

Automating text in R, and making the output look human.

Cara Thompson, list(name = “Cara Thompson”, url = list())

An easy trick to sort out all the line breaks when copying text from a PDF

r-how-to

Copy-pasting from a PDF into another format (say, Rmd or qmd or Word) and getting fed up with the line breaks? stringr::str_squish() is your friend!

Formatting subscripts using 📦{ggtext}’s element_markdown()

data-visualisation

r-how-to

Another fun annotation trick within the same plot!

Annotation and axis label tweaks in ggplot2

data-visualisation

ggplot2

r-how-to

Optimising label placement in facetted graphs

Today’s I 💙 R moment: {usethis}

r-how-to

An underrated package that makes so many fiddly things way easier!

Building the Ophelia package

data-visualisation

dataviz-design-system

ggplot2

A look behind the scenes at the process involved in creating a bespoke ggplot theme package for a research group at Cambridge University.

Using transparency to emphasise the story arc

data-visualisation

ggplot2

storytelling

r-how-to

Today’s #rstats #dataviz “make it easy for your readers” tip: use transparency to enhance the storytelling capabilities of your plot.

What are the default margins in ggplot’s theme_minimal() and theme_void()?

data-visualisation

ggplot2

Turns out they are different, but you can easily tweak your code to get the same margins across all your graphs!

Today’s #rstats function I really should have tried before now: `purrr::walk()`

r-how-to

I love a good “for” loop, because it’s very readable, but walk() is more succinct and very readable - arguably more so!

I got some floating stacked bars!

data-visualisation

ggplot2

r-how-to

Or did I…

Just a flight away

data-visualisation

storytelling

ggplot2

My #TidyTuesday contribution this week is a chance to acknowledge how hard it was being “Just a flight away” during the pandemic

Align your axes

data-visualisation

r-how-to

annotations

ggplot2

parameterised-plots

Applying a few formatting tricks and a custom function to make sure the x axes line up nicely across different plots.

Accessibility in dataviz

data-visualisation

r-how-to

ggplot2

Finally got a chance to catch up with MineDogucu’s #user2022 talk on accessibility. Some great tips within a wide-ranging framework, from making resources open and accessible to using example data on a range of topics to coding tips.

Level Up Your Labels

data-visualisation

annotations

ggplot2

r-how-to

Five tips from my useR 2022 poster presentation

Level Up Your Labels: Tips and Tricks for Annotating Plots

data-visualisation

r-how-to

annotations

ggplot2

user!2022 - Poster and Elevator Pitch

Docker, taking notes, and a brilliant tutorial

r-how-to

misc

Brilliant tutorial this morning at _useRconf by rami_krispin and rsangole on using #docker for #rstats users.

Building a textbox to highlight the difference between two points

data-visualisation

annotations

When the x axis is showing dates… turns out it wasn’t too bad!

How to add space around the title of a ggplot the better way

data-visualisation

r-how-to

ggplot2

👉The margin argument from 📦{ggtext}’s element_markdown()

Credit where it’s due: changing the canonical URL of a post

r-how-to

ggplot2

A quick change in the YAML header to keep the search engines happy.

Cara Thompson, list(name = “Cara Thompson”, url = list())

In today’s #rstats adventure I learnt about tidyr::complete()

r-how-to

Running summarise() or count() and want to keep combinations where there are 0 entries? complete() is your friend!

Generative Art for today’s headline

data-art

parameterised-plots

The PartyGate generative art script I created is a gift that keeps giving

How many characters are there in 700000? It depends!

r-how-to

misc

Today’s fun #rstats discovery while working on a client project for rfortherest

Visualising the NYT Bestsellers in this week’s #TidyTuesday

data-visualisation

r-how-to

ggplot2

This week’s #r4ds #TidyTuesday is about the nytimes Bestsellers. I created some shelves containing the books that stayed on the list for at least 1 year. Which 4 books were there for 3+ yrs?

That signature red rectangle above the title

data-visualisation

How did everyone else tackle the challenge of recreating the iconic chart signature from the Econonist?

Five quick #rstats tips I’ve picked up in the plots I made for my second #30DayChartChallenge

data-visualisation

r-how-to

annotations

ggplot2

The one I don’t mention here is that you definitely get faster as you go. These challenges are a great way of building up a library of code and skills you can draw on for future projects!

Git branch switch

r-how-to

misc

For that moment when you realise you’ve made changes you want to keep, but they should have been in a branch

My contribution to this week’s #TidyTuesday is a tribute to the #tidyverse!

data-visualisation

r-how-to

ggplot2

A slope plot using the colours of the tidyverse logo.

Viewing dataframes and tibbles the easy way

r-how-to

Piping the data into View()!

How to make data viz that matches your organisation’s branding

dataviz-design-system

ggplot2

Picking a colour scheme that ties in with a client’s brand or that evokes the subject matter behind the data is what allows datavisualisations to contribute to, rather than detract from, the main story the client is seeking to tell. This post covers both the design steps and the coding steps involved in creating bespoke colour schemes.

My first #TidyTuesday of 2022: Chocolate!

data-visualisation

annotations

ggplot2

…in a week where I bit off more than I could chew and not enough of it was chocolate.

New year, new laptop, new library location, new version of R!

r-how-to

data-visualisation

Eek? Starting again wasn’t nearly as painful as it used to be, thanks to {installr} and the generosity of people posting solutions online.

Introducing my new #rstats 📦: {monochromeR}

r-how-to

data-visualisation

An easy way to create, view and use monochrome colour palettes.

The beauty of not knowing

data-art

Enjoying some outputs from my aRtful_bot

Turning photos into paintings with R

data-art

data-visualisation

A fun exploration of image sampling

A new adventure!

data-visualisation

storytelling

ggplot2

Sleep while the baby sleeps, or do some

Visualising data from Billboard and Spotify

data-visualisation

ggplot2

Making it look like a sound wave was a fun challenge with this one

Setting up a generative art project using

data-art

r-how-to

ggplot2

For the last wee while, I’d been wanting to explore the fascinating field of Generative Art and add a continuous deployment project to my portfolio. Enter the @aRtfulBot, a Twitter bot I created to explore both of these at once!

Cara Thompson, list(name = “Cara Thompson”)

Alignment cheatsheet

data-visualisation

ggplot2

annotations

I’ve used {ggtext}’s geom_textbox() a lot in my recent data visualisations, but, every time, I end up resorting to a bit of trial and error to get the alignment just right. Time to create a cheatsheet that will be useful to my future self, and hopefully to a few others also.

Welcome to Pars pas les mains vides!

storytelling

Welcome to my blog! Its title, 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, datascience and dataviz, and share them with others who may find them useful for their own adventures.

30DayChartChallenge - Day 24: Time series | Monochrome

data-visualisation

Combining many of the things I love in a monochrome dataviz celebrating J. S. Bach, the master of chromatic explorations.

30DayChartChallenge - Day 23: Time series | Tiles

data-visualisation

annotations

Keeping this one simple after realising adding the dates into the x axis would make it rather busy! Regime changes in France from 1610 to today.

30DayChartChallenge - Day 22: Time series | Animation

data-visualisation

Couldn’t resist. I timed a few of our walks and made us race against Frodo and Bilbo, just to see who walks fastest. Turns out, hobbits are not very fast.

30DayChartChallenge - Day 21: Time series | Downwards

data-visualisation

data-art

storytelling

Keeping things simple today to try to get ahead as the shift to 0.5 is imminent,🤞!

30DayChartChallenge - Day 18: Relationships | Connections

data-visualisation

Inspired by the ABIDE series at https://www.twitter.com/stcsfreechurch I decided to plot where each of the Psalms we’re studying crop up in the Gospels.

30DayChartChallenge - Day 20: Time series | Upwards

data-visualisation

ggplot2

Recycling another

30DayChartChallenge - Day 19: Timeseries | Global change

data-visualisation

ggplot2

Still working on Day 18, but here’s a #TidyTuesday plot I made a few months ago which fits today’s theme: the rise of mobile phones around the world.

30DayChartChallenge - Day 17: Relationships | Pop culture

data-visualisation

storytelling

Using a bump plot to map out the relationships within the band Fleetwood Mac

30DayChartChallenge - Day 16: Relationships | Trees

data-visualisation

annotations

ggplot2

After yesterday’s marathon effort, I’m taking a shortcut today and recycling another of my #TidyTuesday contributions in which I used machine learning on the {palmerpenguins} dataset to illustrate Decision Trees.

30DayChartChallenge - Day 15: Relationships | Multivariate

data-visualisation

storytelling

Spent way too long on this one, looking for a good dataset to illustrate this concept!

30DayChartChallenge - Day 14: Relationships | Space

data-visualisation

storytelling

ggplot2

Recycling one of my #TidyTuesday contributions which fits with the today’s theme: exploring the relationships between age of first space mission, dates, gender, and a few other things.

30DayChartChallenge - Day 13: Relationships | Correlation - Exploring antenatal care and GDP

annotations

data-visualisation

An annotated correlation using UNData, highlighting a few important outliers

30DayChartChallenge - Day 12: Distributions | Strips

data-visualisation

More rain data, but with an international comparison this time!

30DayChartChallenge - Day 11: Distributions | Circular

data-visualisation

annotations

Visualising rain data in Edinburgh with an aesthetic borrowed from the festival

30DayChartChallenge - Day 10: Distributions | Abstract

data-visualisation

data-art

After yesterday’s monster plot, I went for something more refined: playing with letters, fonts and colours based on Kandinsky’s first abstract painting.

30DayChartChallenge - Day 9: Distributions | Statistics

data-visualisation

storytelling

Using the wonderful 📦{dinosauRus} and a combination of https://www.twitter.com/thomasp85’s {gganimate} * {ggfx} and {ggside} to illustrate that statistical summaries sometimes miss the bigger picture.

30DayChartChallenge - Day 8: Distributions | Animals

data-visualisation

annotations

{ggExtra} and direct annotations

30DayChartChallenge - Day 7: Distributions | Physical

data-visualisation

In memory of my grandmother’s love of mis-translations - a map without a map!

30DayChartChallenge - Day 6: Comparisons - Experimental

data-visualisation

Revisiting one of my favourite undergrad Psychology experiments, the Stroop Effect.

30DayChartChallenge - Day 5: Comparisons - Slope

data-visualisation

Back to the Internet access data from #UNData for a simple graph exploring how things have changed since 1990 in Europe.

30DayChartChallenge - Day 4: Comparisons - Magical

data-visualisation

A waffle graph that doesn’t always make me new friends

30DayChartChallenge - Day 2: Pictogram

data-visualisation

Some more {ggfx} along with {ggimage}, exploring proportions of boys and girls in classrooms.

30DayChartChallenge - Day 3: Historical Comparison

data-visualisation

Scraping the text of historical documents with {rvest} to visualise the relative importance of common words

30DayChartChallenge - Day 1: Part-to-whole

data-visualisation

Data from UNdata on internet use around the world.

A Shiny App to make text sing

storytelling

I built a quick Shiny App to help users apply Gary Provost’s writing advice.

DuBois Challenge: Recreating his innovative spiral graph, and animating it!

data-visualisation

ggplot2

Revisiting DuBois’ data visualisation was a masterclass in innovative techniques for creating compelling visualisations which push the boundaries of “normal” visualisations while being intuitive to their intended audience.

Arists, their lifespans, and their most productive times

data-visualisation

data-art

ggplot2

Creating storytelling data art about artists - how meta.

Visualising the rise of the use of mobile phones

data-visualisation

annotations

ggplot2

Another #TidyTuesday contribution, reminiscing about the old Nokias.

Visualising crop proportions - treemaps and line graphs give a different impression!

data-visualisation

r-how-to

storytelling

ggplot2

Catching up with #TidyTuesday data after prioritising a few other things. Having grown up in https://en.wikipedia.org/wiki/Beauce,_France I couldn’t not do this one.

Turning a 16th century theological data visualisation into an interactive network graph

data-visualisation

annotations

r-how-to

ggplot2

This hierarchical graph looked too structured to the people talking about it. So I reworked it into something a bit more organic…

Visualising trends of chattiness and IMDB ratings in Avatar: The last airbender

data-visualisation

ggplot2

storytelling

r-how-to

Using ggplot to combine traditional plots, polar bargraphs and images in a data visualisation to tell a story about a group of more or less chatty characters

Machine learning, penguins and explanatory data visualisations

data-visualisation

annotations

r-how-to

ggplot2

An annotated data visualisation to illustrate the decision-tree model classification of penguins into species based on their flipper and bill lengths

A map-based data visualisation with dancing emojis

data-visualisation

ggplot2

The feral pigs caught my eye in the Brisbane dataset, and then things got rather silly.