“Chatty Women”, iterative data, and the tribulations of fitness gadgets (Andy’s Digest, vol 1)

A great pleasure in life, is conuming amazing content across the web. Here’s 3 great things I’ve read in the last two weeks which help me connect data with things happening in the wider world. I hope you like them!

(from The Economist)
  • 5min read: Chatty women and strong, silent men (The Economist)
    • Why should you read this? First because it’s data-driven diversity and second because it teaches us how to have better conversations with others.
    • tl/dr: An Uber exec resigned over a sexist comment (Paraphrased: “More women on the board? They’ll never stop talking”). The Economist looks to see if any data supports that: it doesn’t. However, the data does reveal fascinating differences between gender’s conversational styles and goals. This is great information for all of us to empathise with others.
(from Periscopic)
  • 5min read: Visualizing Spanish Migration (Periscopic)
    • Why should you read this? This is about iteration with data: the only way to insight
    • tl/dr: It is simply not possible to get the best articulation of your data without exploring it and teasing out the best view through iteration. This article excellently describes the iteration process and how it helped develop the best possible end result.
(from Fitbit)
  • 27min podcast: Human vs Machine: Fitness Gadgets (Bloomberg)
    • Why should you listen? Because AI and machine learning aren’t good enough to threaten humans yet.
    • tl/dr: Fitness gadgets suffer from Dead-End Dashboard problems but they’re getting better. This podcast pits them against a real fitness trainer. The conclusion? Like most AI applications, they’re far from fully functional and for the foreseeable future. The point is that for now, augmenting human ingenuity is the right path forward for AI and ML.

Let me know your thoughts – do you have any comments? Do you want to see more posts like this?

Is Trump signing more executive orders than anyone else?

[UPDATE: I will be delving into my motivation for building this viz, and how I did it, in a #MyRecentViz webinar on Feb 7th]

Click to see an interactive version

As a left-leaning citizen, I watch in horror as Donald Trump dismantles Obama’s legacy. As a British person, the reports of Trump’s signing of a multitude of executive orders, actions, and presidential memoranda leave me in shock. How can a nation have a system where a president can pass laws without any checks or balances?

“Surely this level of activity is unprecedented,” I think.

Wary that drawing a conclusion based on media reports alone is risky, I sought the data to compare Trump to previous presidents. I got the data from the excellent American Presidency Project.

My data-driven, fact-based conclusion is disheartening: Trump is merely following the lead set by Obama 8 years ago. Barak Obama signed 9 executive orders in his first 10 days. He was the first president to get the pen out to dismantle the previous president’s legacy. Prior to Obama, George W signed two orders in the first ten days. Before him Clinton signed three.

8 years ago, I probably applauded those executive orders Obama signed. Little could I predict that he was setting a precedent that could be used by any future president.

For more on executive orders, Jurist has a good summary. About.com has a good summary of the difference between executive orders and actions.

100yrs of data viz: and we’re still making mistakes – #data14 preview

Don't go overboard on your infographics
Don’t go overboard on your infographics

I’m off to Seattle next week for my 11th Tableau Conference. I’ve spoken at each one I’ve been to but have rarely been as excited about the talk I’m giving, and a new blog that’s going to follow.

The session: 100 yrs of data visualisation and we still make the same mistakes (Thu, 10.45am, room 6B)

Answer me this: who wrote the definitive book about effective data visualisation? Alberto Cairo? Stephen Few? Edward Tufte? They certainly wrote best-selling books. But they were late to the party.

In fact, the first, and I will argue, the best, book on effective data visualisation is 100 yrs old this year. That’s right. 1914. The year of the first commercial airline flight, the first skyscraper in Seattle, and first official Mother’s Day in the US.


We had all the answers 100 years ago.
We had all the answers 100 years ago.


Graphic Methods for Presenting Facts was written by Willard C Brinton.

My session is based around that book. We’re going to look at

  • how his guidelines for effective best practice are just as valid today.
  • how technology has changed but is always one step behind our imaginatoin
  • how society has changed but the need to share data hasn’t.

By the end of the session I hope everyone will be inspired to ensure that, in 100 more years, our great great grandchildren are visually literate.

The blog: #100yrsOfBrinton (over on tumblr)

Which map pin should you use?
Which map pin should you use?

In just one hour I won’t possibly be able to pack in everything there is to know. Today I am launching a new tumblr, 100 Years Of Brinton. Over the next few months, I’ll be posting snippets from the book. My hope is these will inspire and entertain you. The ultimate goal? For everyone, not just dataviz nerds like me, to know about Willard C Brinton’s amazing book.

I hope you come along to the session. If not, follow the blog, and let me know what you think using the hashtag #100yrsOfBrinton.


Next Top Model

The power of social networking has struck again. Next are seeking their next Top Model. Computer Science graduate Roland Bunce is the runaway favourite so far. I took the data of the top five entrants and created this viz to emphasize how big a lead he’s got. Go Roland! More details at the Guardian.