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Three short lessons on comparisons

I like this New York Times graphic illustrating the (over-the-top) reaction by the New York police to the Eric Garner-inspired civic protests during the holidays. This is a case where the data told a story that mere eyes and ears couldn't. The semi-strike was clear as day from the visualization.

There are three sections to the graphic, and each displays a different form of comparisons

The first chart is the most straightforward, comparing the number of summonses this year to that of the same time a year ago.

Nyt_nyc_summonses1


One could choose lines for both data series. The combination of one line and column also works. It creates a sensation that the columns should grow in height to meet last year's level. The traffic cops appear to have returned to work more quickly. That said, I don't care for the shades of brown/orange of the columns.

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The second chart accommodates a more complex scenario, one in which the simple year-on-year comparison is regarded as misleading because the overall crime rate materially dropped from 2013 to 2014. In this scenario, a before-after comparison may be more valid.

Nyt_nyc_summonses2

The chart has multiple sections and I am only showing the section concerning summonses (The horizontal axis shows time, the first black column being the first ten months, and the other orange columns being individual months since then. The vertical axis is the percent change from a year ago.).

The chart shows that in the first ten months of 2014, before the semi-strike, the number of summonses issued was already slightly below the same period the year before. Through the dotted line, the reader is invited to compare this level of change against those in the ensuing months. How starkly did the summonses rate fell!

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The final chart reveals yet another comparison. Geography is introduced here in the form of a proportional-symbol map.

Nyt_nyc_summonses3

Again, you can't miss the story: across every precinct, summonses have disappeared. This chart is very helpful to making the case that the observed drop is not natural.

 

 

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