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Free NYU session on data visualization

As some of you may know, NYU is launching a Certificate in Analytics and Data Visualization, which I have helped put together. The course offerings are shown here. If you need to visualize data for work, this is the program designed for you. Data visualization techniques are even more important in the age of "Big Data". In addition, our approach emphasizes the need to think about your data before you visualize them.

On 12/12, Dona Wong (author of the Wall Street Journal Guide to Information Graphics) is offering a free lecture called "Telling Compelling Stories with Data". This is a chance to hear from one of the top people in dataviz. The link with more information is here.



Involuntary head tilt

A data graphic's first mission is communications. Looking cute should not come before. This one is a big fail by MIT Technology Review (link).


What makes the designer want to tilt the reader's head?

This chart is unreadable. It also fails the self-sufficiency test. All 13 data points are printed onto the chart. You really don't need the axis, and the gridlines.

A further design flaw is the use of signposts. Our eyes are drawn to the hexagons containing the brand icons but the data is at the other end of the signpost, where it is planted on the surface!

Here is a sketch of something not as cute:


Notice that I expressed time as years, and undid the log-transform on the axis of users. The mobile-related entities are labelled red. The dots could be replaced by the hexagonal brand icons.


The other two charts on the same page have their own issues. Health warning: your head may tilt.


Light entertainment: Behold the 10 percent change!

Reader Orjan L. sent in this Swedish delight:


It's on the last page of this report, and I'm told it's about the number of weapons seized by Swedish customs each year.


On p. 8, I found a hockey-stick chart:


Sweden in ecstasy.


For those who love cross-over charts, look no further than p. 3 which has a reverse hockey stick.


A letter to high-school students

Imagine Magazine, a youth-focused journal by Johns Hopkins's Center of Talented Youth, invited me to contribute an article in celebration of statistics. I try to convey the fun and joy of working with numbers and charts.

You can read it here, starting on p. 22. While you're at it, the rest of the magazine is really great too, and I hope we're able to influence at least a few youngsters to take up math-stats as a career.

Please forward to kids and teachers!

Graph redesign is hot

Joe D., a long time reader, points us to a few blogs that have been active creating redesigns of charts, similar to how we do it here.

First up, here are some examples from Storytelling With Data (link).

This example transformed a grouped bar chart into a line chart, something that I have long advocated. I'm still waiting for the day when market research companies start to switch from bars to lines.

Stwd_Student Makeover 2


Jorge Camoes, also a long-time reader, produced a redesign of a chart on military spending first printed in Time magazine. (link)


Dual-axis plots have been pilloried here often, especially when the two axes have different and incompatible units, as in here. As usual, transforming to a scatter plot is a good first step, which is what Jorge has done here. He then connected the dots to indicate the time evolution of the relationship. This is a smart move here just because the pattern is so stark.

The chart now illustrates an "inflexion point" in 2000. Prior to 2000, troop size was decreasing while the budget was stable. After 2000, budget increased sharply while troop size remained relatively stable.

Now peer back at the original chart. You can discern the sharp decrease in troop size over time, and the sharp increase in budget over time, but separately. The chart teases a cross-over point around 1995 which turned out to be misleading. This is a great illustration of why dual-axis plots are dangerous.

What's in a cronut? Let me find out

Analyticsseo_gaReader Ross S. did not join the line for this cronut, illustrating the popularity of different makers of tracking software on 1.3 million websites.

Original by Analytics SEO is here.


The biggest beef I have with this cronut is the quality of the data. As I read their description of the underlying data, I see several red flags.

The analysis is hobbled by ignoring the competitive landscape in tracking software. Google Analytics carves out a huge share of the market by virtue of offering a richly featured product for free. (They justify this by establishing a gigantic spying operation on unsuspecting users.) However, industry insiders know that Omniture (owned by Adobe) is the heavyweight enterprise solution, with a complete feature set.

In other words, most of the 670,000 "customers" of Google Analytics are tiny websites; in addition, a lot of large websites also maintain Google Analytics in addition to Omniture since the former is free. It would be great if the researcher gives us one of two alternative views of market share: the share of revenues in the tracking software market; and the share of e-commerce revenues represented by the customers of each tracking software vendor. These two views give a fuller picture of the competitive landscape.

You'll notice this is the same game Google is playing in the mobile universe. Android has the most users but Apple makes the bulk of revenues.


The SEO agency says the chart is "based on 1.3 million e-commerce websites in May 2013". Are there really 1.3 million websites out there selling us stuff? How do they define e-commerce? Is NYTimes.com an e-commerce website, for example? Or facebook.com for that matter?

In the summary, they made a pretty startling claim--that "a large number of websites have no tracking software at all". The only problem is readers can't find out what proportion of websites don't track users. The data in the cronut excluded sites without tracking, which is a big problem.


Here is the link to the annual Top 500 Retailers report by Internet Retailer magazine. In Sep 2011, they found that 217 out of the top 500 use Omniture, 161 use Google Analytics, and 103 use Coremetrics (now owned by IBM).

Another place to look for corroborating evidence is Google Trends, which measures the popularity of search keywords. The relative order of the major vendors (excluding Google Analytics) does not match well with the data shown by Analytics SEO.


Compared to:


Coremetrics is way down in the list compiled by Analytics SEO.