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Joe Leider

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Data visualization

Murder in Chicago: Finding the Ferguson Effect in 10 Graphs

March 8, 2017 by 1 Comment

On August 9, 2014, Michael Brown was killed in Ferguson. Since that time, murder rates in some cities have spiked. Our current President has extrapolated a society in chaos from that spike. Indeed, we’re tempted to draw the conclusion that the Ferguson killing caused the spike in murder rates. While proving a causal relationship can […]

Filed Under: Data visualization

Five visualizations of Bend, OR half-marathon results

April 27, 2015 by Leave a Comment

Yesterday I ran a half marathon in Bend, Oregon, so I’m going to keep it a little lighter. I trained a lot using this excellent free program from Hal Higdon. Because the results were posted in a nice simple table, I thought I’d do a few visualizations to see how well I did in addition to […]

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The best- and worst-valued housing markets

April 21, 2015 by 2 Comments

In a previous post I looked at price-to-rent ratios in major markets. Like a PE ratio for stocks, price-to-rent ratio is a decent benchmark for judging whether housing markets are over or undervalued. There are caveats to this, of course, including prevailing mortgage rates, real estate taxes, income tax giveaways, etc. But for it’s simplicity, I […]

Filed Under: Data visualization

Salon going off the rails: a case of using and presenting data badly

April 14, 2015 by Leave a Comment

I don’t like to define myself as liberal or conservative. On some issues I’m very liberal: social issues like gay marriage and abortion. On some issues I’m conservative: simplifying the tax code, cutting corporate tax rates, eliminating foreign earnings taxes. On some issues I’m libertarian: legalize marijuana (and other drugs, for that matter). And on […]

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The seasonality of Chicago crime

April 9, 2015 by Leave a Comment

I wrote a couple posts on Chicago crime: 13 data narratives and Chicago crime by hour. But the data are so interesting that I wanted to dig deeper into the seasonality of Chicago crime. Before I was using trendlines to show this, but by switching to a color-box like below, we can more easily compare […]

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Visualizing crime by hour in Chicago

April 2, 2015 by Leave a Comment

A comment on my blog from spreadsheetjournalism suggested that looking at Chicago crime data in Excel might yield more insights because you could better see crime by hour. This is certainly possible in Tableau, and the visuals will bring quicker insight in rapid-fire succession when compared to an Excel pivot table. Before delving into the data, I suspect […]

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13 data narratives on crime in Chicago

March 24, 2015 by 5 Comments

I recently downloaded a Chicago crime data set at 1.2 gigabytes and around 5.75 million rows of data (1 for every crime committed since January 2001). First of all, kudos to the City of Chicago for making this data public. More kudos to Tableau for designing a product that makes it possible to quickly visualize […]

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Failed states, failing cities? Comparing murder rates in American cities

March 23, 2015 by Leave a Comment

We hear a lot about failed states, and we wonder what we as Americans should do. Sometimes the threat of a failed state goads us to intervene abroad to protect our interests. That might mean American business interests, it could mean preventing the setup of terrorist safe havens, or maybe we just want to give […]

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Housing part III: are we back in the bubble?

March 18, 2015 by Leave a Comment

In my initial article on house-price-to-rent ratios, I looked at how major US markets compared to each other in terms of one of my favorite real estate value metrics – price / rent (using Zillow’s ZHVI / ZRI as a standin). In part II, I examined recent trends by region for that same metric. Now I […]

Filed Under: Data visualization

The most expensive hospitals in America – a data visualization case study

March 13, 2015 by Leave a Comment

I recently came across a fascinating data set – the Inpatient Prospective Payment System (IPPS) Provider Summary for the top 100 diagnoses. The name is quite a mouthful, as is the data on charges at 3,332 hospitals for the top 100 diagnoses. Unfortunately with so many attributes, it’s hard to spot a good story. First I’ll […]

Filed Under: Data visualization

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