GIS Mapping: Part II
Hello everyone! Last week, I posted on using Google Earth for GIS Mapping as a way to visualize data and make a convincing argument to funders, doubters, and assorted naysayers (or supporters, I suppose). Today, I’d like to talk about a newer tool that is available for the same purpose: Tableau and Tableau Public. To demonstrate, I’ve made some sample maps that show cases closed by Montana Legal Services Association (MLSA) in 2012.
There are a few paid versions of Tableau – Desktop Personal, Desktop Professional, and Server – that you can use, depending on what your needs are. However, the free edition (Tableau Public) worked great for me.
Tableau vastly simplified the data visualization process; really, it’s incredible that I got it for free. After downloading and opening the software, I imported an Excel spreadsheet of MLSA’s case data from 2012. Tableau took the column headings as titles, separating my data into maneuverable pieces (such as County of Residence, Race, Legal Problem Code, and so on). These it placed in a column on the left-hand side, along with several “Measures” like Number of Records. I could drag and drop these categories to a workspace in the middle, specifying which categories were “Columns” and which were “Rows,” or which to use to alter the size and/or color of my chart.
I could also choose which type of chart, graph, or map to display (and the software gave some tips about which was appropriate based on what kind of data I wanted to input).
After dragging and dropping for a while – with very quick updates to the charts or maps I was working on – I created a few charts just as examples:
This pie chart shows cases closed by primary staff responsible for the case. To create this, I placed the “Primary Assignment” category in the “Color” field, and “Number of Records” in the “Angle” field.
This bar graph shows the number of records for each attorney at MLSA in 2012. To create this, I placed the “Primary Assignment” category in the “Columns” field, and “Number of Records” in the “Rows” field.
Finally, I created the type of map I did in my last post – but it was much easier. I added “County of Residence” to the “Columns” field, from which Tableau generated “Longitude” (in the “Columns” field) and “Latitude” (in the “Rows” field). I put “Number of Records” in the “Color” field, and presto! A filled map (what I referred to in the last post as “thematic;” Tableau can also create “symbol,” or what I called “point” maps).
There was a problem in that Tableau didn’t recognize the names of many of the counties. To correct this, I just had to specify that I was using data from Montana. I clicked on the number of “unknown” pieces of data in the bottom right-hand corner of my workspace, indicated that I wanted to “Edit Locations,” and at the top of the pop-up window chose “Montana” as my “State/Province.” After that, the only ones Tableau couldn’t identify were those that were invalid county names to begin with (such as “Out of State” and a few with no information). Those that are blank on the map below are counties for which MLSA didn’t handle any cases in 2012.
Next, I noticed that Tableau gives you a few options with how to display your map. You can choose whether or not to display things like roads, various borders, and place names.
Tableau also allows embedding your map (click File > Save to Web As, then create an account and it will give you both a link and embed code) so that it can be viewed and manipulated by visitors to your site. Here’s the map I created:
All in all, I really liked Tableau (if you couldn’t tell!). It’s very powerful, while still being easy to use and customize.
To be honest, I was going to discuss several pieces of software in this post. However, Tableau worked so well and the others were so difficult for me to get working that I decided to keep it short and sweet. If you are interested in shopping around, though, here are the other services that I was looking at:
For more on GIS Mapping and data visualization, check out the work done on GIS by Legal Services of Northern California, as well as books by Edward Tufte and Mark Monmonier. If you have an extraordinary amount of data or want expert help, get in touch with DataKind – they have a team of data scientists who can work directly with clients.
Happy mapping, everyone!