Design & Analytics' Blog

Visualizing the History of Philosophy as a social network: The Problem with Hegel

How Important is Hegel?!

I was surprised I hadn't seen this graphic at Drunks and Lampposts made with Gephi until a friend posted it on facebook last week.  The original is here, and here's my version:


Graph History of Philosophy

Using a scrape of the data behind wikipedia's sidebar for philosophers, Simon Rapier put together a fantastic visualization of the schools and interconnections among philosophers.  Griffsgraphs followed up by expanding the scrape to the entire network of influencers and influenced on wikipedia.  Both of these are insightful humanities studies in graphs and visualization---even though the algorithm wasn't told which common ideas link Hegel and Marx, it saw that they were similar enough to be grouped together (shown by making them the same color), and that the way Hegel influenced, say, Husserl, was different enough to warrant another school, simply by observing a different group of people followed them.

That's a solid aggregation of a lot of humanities information.  Who knew Skynet's tweed jacket had patches on the elbows?

However, looking at the original graphs on D&L and Griffs, I was struck that...

CFNAI the most underrated indicator according to ishares

According to the ishares blog, the Chicago Fed National Activity Index (CFNAI) was recently named the most underrated index for measuring the US economy's health.  I wholeheartedly agree.  I co-ran this beauty when I worked at the Fed in 2008-2009 and automated its graphing in Matlab.  If you look back in the archives from around then, you'll see...

Complex causality for 37signals NYT opinion; or Tigers

I really liked this story on the 37signals blog yesterday where Jason Fried explained the process of seemingly serendipitous events that led to his being asked to write an opinion piece in the New York Times.  I've been working with network visualization lately and turned his story into the graphic below, which they've kindly posted back to the 37 signals blog

Image Showing how to get into the New York Times

Opening for Clients; Hire me

I have an opening to take on more hours of client work beginning in mid-September.  Please feel free to contact me if you're looking for support in forecasting, automation, quantitative design, social network analysis---or anything I've written about here.

Game of Pickaxes Book Project from Ribbonfarm

Mr. Tempo himself is working on a new project called Game of Pickaxes.  You can sign up for his early-phase mailing list on the book's pre-launch site.

I designed this early draft of the cover and launch site---well, as well as the final cover to Tempo.  Over the summer, I'll collect and post a series breaking down how I structure the iterations of a cover design process, focusing on metaphor in quantitative designs.  In the meantime, sign up for the mailing list, and read the full announcement at Ribbonfarm (and thanks for the hat tip, Venkat!).

Beard line: Time Series in R (Part III)

In Part 2, we showed how to add recession shading to a plot of American Beards over time, and did some diagnostics to check whether 19th Century Americans grew recession beards. (Spoiler alert: it appears they did not.)  In Part 1, we showed how to plot the series in the first place.  Today, we're going to look at the beardly trend over the period.  We all know about the gilded age popularity of mutton chops and sideburns, but were full beards on the rise or on the decline between 1866 and 1911?  And more importantly, what can this period tell us about beards of the future (in the past)?!

What you'll learn

  • How to apply linear smoothing to a time-series plot in ggplot2
  • How to interpret that and how not to interpret that.  (The difference between interpolation and extrapolation.)
  • Whether beards were getting "trendier" or trending less during the tail end of the 19th Century.
  • What date we're all going to have beards.

Weird Data Champion and Google Search

Checking my web analytics, I noticed that Design & Analytics is now in the coveted #4 google hit position for "weird data sets."  That means I'm probably pretty close to getting Nike sponsorship and my face on a Wheaties box in the data olympics category.

Recession Beard? Time Series in R (Part II)

In Part I, we showed how to plot a time series of the change in American beards over time, using a dataset from Robert Hyndman's time series data library.  Today, we're going to look at whether the dramatic changes in American male beardfulness seem related to the economy.  Did Americans grow recession beards in response to the Panic of 1873?  Out of work, did they forgo their frequent trips to the barber (since Gillette didn't invent the personal safety razor until 1904 so they could do it themselves)?  Did they go on their job interviews with a face full of mutton chops and just never get called back (by telegram)?

What you'll learn

  • How to apply recession shading, according to the NBER's recession dates, to a time series---easily.
  • How to change the color of the recession shading
  • Whether 19th century gentlemen grew recession beards after losing their jobs in algo trading, you know, just taking some time off to study graphic design for a little bit.

How many veterans are there? Memorial Day data

The short answer is there are about 21 million American Veterans as of 2012. As a total, that's about 6.8% of the US population.

For comparison, that's about...

American Beards Over Time: Time Series in R (Part I)

If you use R for time series analysis, chances are you've used Robert J. Hyndman's excellent forecast tools.  I recently stumbled on his time series data library where I found just the data set I've been looking for to show some R time series plotting tricks:

It's the percentage of American men with full beards reported annually.  Nothing serious here, but absurdly perfect for a set of posts to share a couple things that took me a while to learn when plotting in R.

What you'll learn

  • How to grab data from a plaintext source on the web, stripping header information
  • How to convert a list of data with a known start time and end time into an xts time series object
  • How to convert xts to a data.frame for plotting in ggplot2
  • Aesthetics for red data points with dotted line interpolation
  • How much American beardfulness there was in the late 19th century and early 20th.


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