I’ve posted before about the upcoming launch of Docket Dog, a case watching service for Arkansas state court cases. To me, one of the interesting things coming out of Docket Dog is the ability to look at different metrics for case filings in Arkansas.

I have been learning the Python programming language, which has some good visualization tools available for it. My latest exploration has been using Python to create state maps. I found this awesome tutorial by a guy with an equally-awesome name (Nathan, of course!). I also wanted to view metrics per capita, so I downloaded the latest US Census data.

I wanted to figure out which Arkansas counties were the most sue-happy. So, looked at the total number of cases filed in each county, divided by the population, and plotted the result. Each color band is a multiple of the average for that year.

2015 cases per capita. Click to enlarge.
2015 cases per capita. Click to enlarge.
2014 cases per capita. Click to enlarge.
2014 cases per capita. Click to enlarge.
2013 cases per capita. Click to enlarge.
2013 cases per capita. Click to enlarge.
2012 cases per capita. Click to enlarge.
2012 cases per capita. Click to enlarge.
2011 cases per capita. Click to enlarge.
2011 cases per capita. Click to enlarge.
2010 cases per capita. Click to enlarge.
2010 cases per capita. Click to enlarge.

What do you make of this? Clark County, my old stomping ground, is average from 2010 to 2012, but is well above that the last couple of years.

Why do you think certain counties are more litigious than others?

Nathan here. I’m back for a guest post with some new tricks I’ve learned at my new job from some of the researchers at UAMS. I’ve having a blast getting an inside look at cutting-edge biomedical research. This post looks at some data visualization about the time it takes to resolve civil tort cases in Arkansas.

Background:

One of the researchers has a master’s degree in computer science, and I picked his brain a little bit about what software packages he likes to use. He prefers python to Perl (which I like) because python’s research libraries are easier to use.

I took his recommendations to heart, and I’ve been tinkering around with the Anaconda python distribution with data I’ve gathered for another project I’m working on releasing very soon: Docket Dog. It’s an Arkansas state court notification system. I used the data mining application Orange to perform some data visualization on the types of civil cases my dad and brother handle.

Arkansas Tort Case Length Analysis:

I took a look at over 98000 tort cases available electronically from the Administrative Office of the Courts for which I could calculate an end date. This is what the time frames look like:

Pendency of Arkansas tort cases in years. The scale is 20 years wide. Click to enlarge.
Pendency of Arkansas tort cases in years. The scale is 20 years wide. Click to enlarge.

As you can see, civil court cases can take several years to resolve. We’ll see what the averages look like here in a few minutes with another chart.

In the meantime, there are several interesting patterns that appear in this chart. For instance, on the first line for product liability cases, there are several vertical bands around 9, 12, and 14–16 years. I haven’t looked into this, but I suspect each band probably represents a settlement of a specific type of cases, like Firestone exploding tire cases, Pinto exploding car cases, or something similar.

The declaratory judgment (dec action) line is notably shorter overall than the others. Again, I haven’t researched this further, but I would expect this is due to the fact that dec actions don’t involve juries and are usually about a specific question of law. For instance, lots of dec actions involve whether there is insurance coverage for a particular event or not (the hilarious Luther Sutter v. Dennis Milligan dec action notwithstanding). 

Now, on to the next chart. This is called a box chart:

Comparison of median Arkansas tort case values over the last 20 years. Click to enlarge.
Comparison of median Arkansas tort case values over the last 20 years. Click to enlarge.

This chart is broken up into quartiles. The light blue box represents 50% of all cases. So, 50% of motor vehicle collision (MVC) cases are decided within 2 years, with the median value being 1.6 years. (Median means the middle value; if there were 101 cases, for instance, the median value would be the 51st value). The average MVC case length is shorter at just over 1 year.

The dark blue lines represent maximum values, excluding outliers. The dots out to the right of the graph represent those outliers, which extend out to 20 years.

What’s the bottom line? For 3/4 of tort cases, you can expect resolution to take at least 6 months to 3 years. Another quarter of cases take up to 4 years or so. And, there are always outliers that can take many, many years to reach ultimate resolution.

What questions do you have about this analysis?

I like to tailgate at Arkansas Razorback games, especially in Little Rock, even though we’ve been abysmal there the last 6 years or so. Over the years I’ve developed a list for my tailgating gear so (hopefully) I don’t forget anything. I’m sharing it here (download link here) to see if you have any suggestions. Please let me know in the comments.