Hi, I'm Richard

Data analyst & storyteller.

I specialise in business intelligence, visualisation, analytics, data mining and SQL wrangling. Which is a wordy way of saying I deliver insights from numbers.

This is a personal diary of data visualisations and insights I enjoyed making.

Nationwide House from Lidar data

A model of Nationwide House - 3D render of my office made with 1M DSM Lidar data from Defra, visualised with new free tool Aerialod. Nov '19

Share of vote in UK general elections, 1918 - 2017

One hundred years of British politics - line chart race built with a new dataset on general elections by consituency. Viz using Flourish.Studio, polished in Photoshop. Sep '19

Inc. 5000 Europe

Inc. 5000 Europe interactive - jitter plot revealing a sector-by-sector view of the fastest growing companies in Europe. Made with Tableau and this data.world dataset. Sep '19

Business mountains

Business mountains - a Kepler.gl map showing registered office addresses. It showed up an unusual spike of business registrations in Warrington, and attracted a ton of explanations from the LinkedIn community. Jul '19

Nia Franklin, Miss America 2019

Miss America Tableau interactive - I stumbled on this little dataset at data.world and used it as a way to practice designing mobile friendly viz "on brand". It's also the first time I've used some speed optimisations in Tableau, for a more fabulous online experience. Jul '19

Who we name in our wills

Bar chart race - animated racing charts are in vogue so I joined the party with a view of legacy income to top charities. A project for Wood for Trees, created with Flourish, Active Presenter and Photoshop with data from The Charity Commission. May '19

Tesco company results

Company results sankey - inspired by a similar visualisation from Chartr. These charts can often get confused and hard to read, but this is a really nice implementation. Every little helps. Apr '19

Home ownership in the UK

Power BI story - an experiment using a dashboard and little animation to tell a story with Microsoft's free BI tool. Elements of it worked, but it's still hard to create a polished experience with this platform. Process notes here. Apr '19

House prices vs average UK salary

Animated heatmap showing housing affordability in England. This was a mashup of data from the house price index and ONS annual survey of hours and earnings. Visualisation in Tableau, post production animation in Photoshop. The heatmap style is simple, compelling and tells a lot of stories. Twitter seemed to like it. Feb '19

How to pimp adjacent bars

Adjacent bars are almost never easy to read and this animation shows how a simple switch to overlapping bars produces a much classier, cleaner chart. It's also very easy: Here's how to do it in Excel, Tableau and Power BI. Jan '19

How to pimp a line chart

Short animation showing the small and simple design steps to create charts with more impact. It's driven in no small part by this amazing cheatsheet from Stephanie Evergreen - a great bookmark for better visualisation. Nov '18

Car park occupancy in Bath (Christmas market)

Overlapping bar chart showing the pressure on parking during Bath's annual Christmas market. Data is freely available from the Bath:Hacked city data store, aggregated in Tableau, polished as ever in Photoshop. This research led to a riotous headline in the local paper. Nov '18

Sales of new build leasehold houses

Animated 3D map with data from HM Land Registry and ONS. Map created with Kepler.gl, fly around recorded with Active Presenter. Finished in Photoshop. (Read more about why I made this here) Oct '18

NOx emissions by vehicle type in Bath

Animated column chart showing NOx emissions of vehicles in Bath. Data from BreATHe hack day, wrangled in Tableau, charted in Illustrator, animated in Photoshop. My titling placements irk me now but hacks are rushed, and it resonated enough with the audience to win a prize. Oct '18

House prices by postcode

Choropleth (and PDF report) showing house prices by postcode. This deliberately breaks my rule on viz having an obvious takeaway. I like the confusion and lack of pattern, because that's the point: Contrary to the headlines, house prices simply aren't rising everywhere. Data from HM Land Registry + ONS postcode lookup. Visualisation and report in Tableau. Sep '18

Correlating house price indices

Animated lollipops that try to explain correlation of the major house price indices vs. real sales figures. Data collected by hand from the Halifax, Rightmove, Nationwide and the ONS. Cleaned in Tableau Prep, figure work in plain old Excel, animation in Photoshop. Jul '18

UK housing affordability, 1966 - 2018

Very short video about housing affordability in the UK. This was my first use of Adobe Spark which forces you to concentrate on simplicity. Data by Trussle.com, animated bar chart in Illustrator/Photoshop. Note the use of oversized wording, a trick when creating videos intended for small screens. Jun '18

UK voter apathy

Interactive map built with Flourish using public data from the electoral commission, inspired by a similar US viz from Philip Kearney. This one was pure fun. Apr '18

Ranked column chart that tries to rebalance a view that Brits are critical to the Spanish property market (they actually account for 2% of sales). Data by Kyero.com, wrangled in Chartio, polished in Illustrator, animated in Photoshop. Mar '18

Why I keep this diary...

Data visualisation vexes me daily.

Over the years I've sat through lots of data presentations (and given a few) where audiences died trying to understand great analysis that was badly presented.

It's a heart breaker.

So a while ago I stepped outside of the numbers world, and took a night school class in graphic design. I can't pretend it made me a designer, but understanding a little more about colour theory, typography and grids has really helped in presenting my work.

This page is a personal diary of my favourite visualisations. I hope they're getting better?

I include notes on software and workflow mostly because I've discovered there is no perfect toolset for data visualisation.

Your method will depend entirely on the data, the point you're trying to make, where the viz is going to be presented - and the time you have available.

Critique is welcome, I try to obey just a few rules:

  • If viz needs reading instructions, it's wrong
  • If viz has no obvious takeaway, it's pointless
  • If my mum still doesn't get it, start over

Simplifying the complex is the job.

Enjoy :)