Lab: Choroplethora

The goal of this activity is twofold: to explore how classification methods can change the way we view the data, and to add a little color to set a mood for the maps.

Getting the data

Select a state with at least 30 counties. Retrieve data from NHGIS for your chosen state (at the county level) – you’ll need to choose a shapefile and a data table. Join the data table to your counties shapefile and choose a variable to map (i.e. median income, education level, etc.). Make sure you have data for the majority of your counties – some products, like the ACS (American Community Survey) are not 100% tabulation, and recent years may only have data for a few counties for certain variables.  The data visualization tool at the US Census can help you determine this before you spend a lot of time downloading and joining data – zoom in and select your state, set your variables at the top,  and wait for it to load.

Classifying the data

Set up four data frames, each with the exact same data. All maps should be at the same scale and same extent, using the Small Multiples technique we learned earlier.

For each map, you will choose a different classification scheme of the same variable: equal interval, quantiles, natural breaks and standard deviation. Choose color schemes that set a mood: they work well for the variable chosen, or lead the audience to a deliberate conclusion. Colors don’t need to be identical on all maps, but should be compatible, to build an overall theme.

Normalizing your data

Most of you will be working with data that needs to be normalized, i.e. represented as a percent of total.  If you don’t normalize, you’ll essentially end up with a population map, which tells us nothing about the actual data distribution.  Here’s a quick overview of why.  To do this in ArcGIS Pro or Desktop, use the Normalization field in the symbology settings.

Want to do COVID-19 data?  

  1.  Go to the Esri Disaster Response Hub
  2. Click Download (cloud icon with arrow) and select CSV (Shapefile is points, which won’t work for this lab)
  3. Open the csv and save as an Excel file (.xlsx) as your chosen state name (e.g. Ohio.xlsx)
  4. Sort by Province_State (should be column D), and then delete all the rows that aren’t your state.
  5. Save and close, then proceed to join the tables and make your maps.

Tips for Success

  • Think carefully about your classification choices – the number of classes and the way in which they are represented can impact readability
  • Darker = more is a pretty iron-clad cartographic convention, so think twice before you violate this.
  • Consider whether your data needs to be normalized – the answer is likely yes.
  • Be aware of color acuity issues when choosing your ramps.  ColorBrewer is a great place to find colorblind safe ramps and experiment with how they’ll look.
  • Small multiples is about comparing similarities and differences between maps, so keep as many things the same as possible.
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