travel

75 posts
Revisiting global car sales

We looked at the following chart in the previous blog. The data concern the growth rates of car sales in different regions of the world over time. Here is a different visualization of the same data. Well, it's not quite the same data. I divided the global average growth rate by four to yield an approximation of the true global average. (The reason for this is explained in the other...

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This Excel chart looks standard but gets everything wrong

The following CNBC chart (link) shows the trend of global car sales by region (or so we think). This type of chart is quite common in finance/business circles, and has the fingerprint of Excel. After examining it, I nominate it for the Hall of Shame. *** The chart has three major components vying for our attention: (1) the stacked columns, (2) the yellow line, and (3) the big red dashed...

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Say it thrice: a nice example of layering and story-telling

I enjoyed the New York Times's data viz showing how actively the Democratic candidates were criss-crossing the nation in the month of March (link). It is a great example of layering the presentation, starting with an eye-catching map at the most aggregate level. The designers looped through the same dataset three times. This compact display packs quite a lot. We can easily identify which were the most popular states; and...

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How to describe really small chances

Reader Aleksander B. sent me to the following chart in the Daily Mail, with the note that "the usage of area/bubble chart in combination with bar alignment is not very useful." (link) One can't argue with that statement. This chart fails the self-sufficiency test: anyone reading the chart is reading the data printed on the right column, and does not gain anything from the visual elements (thus, the visual representation...

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Is the visual serving the question?

The following chart concerns California's bullet train project. Now, look at the bubble chart at the bottom. Here it is - with all the data except the first number removed: It is impossible to know how fast the four other train systems run after I removed the numbers. The only way a reader can comprehend this chart is to read the data inside the bubbles. This chart fails the "self-sufficiency...

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Transforming the data to fit the message

A short time ago, there were reports that some theme-park goers were not happy about the latest price hike by Disney. One of these report, from the Washington Post (link), showed a chart that was intended to convey how much Disney park prices have outpaced inflation. Here is the chart: I had a lot of trouble processing this chart. The two lines are labeled "original price" and "in 2014 dollars"....

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Distorting geography to show train travels

Jan Willem Tulp visualized train travel times using distance and color as an indicator. His reasoning: When a train starts running from one station to the next station, conceptually, these two stations will temporarily be closer to each other. And that is exactly what this visualization shows: whenever a train moves to the next station — and only for as long as a train is moving — the origin station...

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Made in France stereotypes

France is on my mind lately, as I prepare to bring my dataviz seminar to Lyon in a couple of weeks.  (You can still register for the free seminar here.) The following Made in France poster brings out all the stereotypes of the French. (You can download the original PDF here.) It's a sankey diagram with so many flows that it screams "it's complicated!" This is an example of a...

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Made in France stereotypes

Kaiser Fung (JunkCharts, Principal Analytics Prep) shows how to use the Trifecta Checkup to identify weaknesses in data visualization, and also how to conceptualize good charts using the same framework. He uses an example inspired by a Made in France poster.

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Education deserts: places without schools still serve pies and story time

I very much enjoyed reading The Chronicle's article on "education deserts" in the U.S., defined as places where there are no public colleges within reach of potential students. In particular, the data visualization deployed to illustrate the story is superb. For example, this map shows 1,500 colleges and their "catchment areas" defined as places within 60 minutes' drive. It does a great job walking through the logic of the analysis...

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