Information can be beautiful

Data visualization is the candy of journalism, for me. It’s fun, intuitive, and gives you an idea of the topic at a glance. I used to be a studio art major and was good at math in high school, so I guess graphs and maps of data always make more sense to me than a wall of text — but I think a lot of people feel the same way. Judging from how often people share these images on Facebook, they seem popular with almost everyone. On the internet, especially, an image or map that grabs your attention and shows you the data in a split second is more likely to be understood than a 1,000-word article that no one will actually read.

One of my favorite sources of data visualization is Information is Beautiful, a site that specializes in this form. Their visualizations are not only informative and well-researched, but graphically stunning — beautiful and well laid-out.

The image at right was on their shortlist of their “best of” from 2014. It shows in a series of three images how in the past Democratic and Republican senators often voted across party lines, but by 2013 senators voted within their own party almost exclusively. You could read thousands of pages of articles describing the polarization of politics without getting the feel for the issue that you get by looking at these images for a few seconds.

Lately I have been conscious of how much a visualization would help me understand issues in my own life. I’ve been thinking of where to move after I graduate in June, and my top cities are Oakland, CA and New Orleans, LA, with Portland as the “stand-by” and San Francisco as the “if I win the lottery.” Looking at Craigslist, I quickly realized that Oakland rent is almost twice as much as it is in New Orleans — a comparable 1BR in a similar neighborhood can be $1500 in Oakland and only $900 in New Orleans.

I looked around for some graphs that could help me get a handle on the actual numbers, but I couldn’t find anything. Graphs published by Forbes and other sites either focused on the 10 biggest cities in the country, or the 10 cities with the most expensive or cheapest rent, none of which included the four cities I was interested in. Some sites allowed me to plot different cities’ rents, but they all had issues — either they included everything within 10 miles of a city, which skews the data, or they only used “average rent” without breaking it down by number of bedrooms or square feet. I finally found a data set on Zillow, but it included hundreds of cities and didn’t include populations, so it was hard to pick out the big cities. I also had no idea how accurate the data was.

The only site I could find that graphed average rent by number of bedrooms listed Portland and New Orleans as having the same average rent for a 1BR, which I know isn’t true. The data was probably thrown off by the fact that Portland has a large section on the East side where rent is a lot cheaper, but it isn’t the area I want to live in. I realized in order to get the visualization I needed, I would have to divide the rent first by square feet and then by zip codes, rather than by city or county boundaries.

After looking through dozens of sites trying to find the right presentation of the data, it really made me realize how wonderful it is when a site like Information is Beautiful takes the time to make an image that is both accurate, well thought out, and graphically intuitive.


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