Data Visualizations from the New York Times

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Everyone loves a good data visualization.  And everyone loves a good data visualization even more if the visualization is interactive.  Unfortunately, I can’t embed an interactive visualization above, but click on it to link to the interactive version.  The circles represent the volume of traffic at airports around the U.S.  Clicking on a circle reveals all of the connecting flights to that airport.  I’m sure you could get this information out of some kind of heinous Excel spreadsheet, but this format is way more engaging.

This is why I was attracted to this year’s Wherry Lecture, which is hosted by the Departments of Statistics and Psychology at Ohio State.  The speaker was Amanda Cox from the New York Times‘ graphics department who spoke about the Times‘ use of data visualizations.  Amanda shared many examples that illustrated the importance of context, how a good visualization sometimes limits the amount of data in order to highlight patterns, and the importance of how the text and the visuals work together.  These are a few of my favorites.

The Jobless Rate for People Like YouNot all groups have felt the recession equally.  This visualization allows you to view trends in different demographics.  The differences can be startling.

One Report, Diverging Perspectives – Employment numbers with “Democrat” and “Republican” buttons that allow you to view the same data through different lenses.

Over the Decades, How States Have Shifted – A look at how each state has voted – Democratic or Republican – with connections to every election since 1952.

Counties Blue and Red, Moving Right and Left – Imagine a map of the wind blowing across the U.S.  Now instead of that wind representing, well, wind, imagine it representing the changes vote margin between Democratic and Republican presidential candidates.

Mapping America: Every City, Every Block – Based on U.S. Census data from 2005 to 2009, you can choose to represent ethnicity, income, housing, education, and other information on a map and then zoom out to view the entire nation or zoom in to view your neighborhood.

All of these examples provide different paths to understanding the data that is represented.  To see some of the other examples in this lecture, check out my Twitter stream (@eslchill) or follow the New York Times Graphics Department (@NYTgraphics).

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