Categorization Methods
I established the categories with the first data set: 2010 Census and 2007-2011 American Community Survey. I will probably update them in the 2020 Census.

Equal Percentile - each category gets the same percent of data. For instance with ten categories, you put 0-10% of the data in the first slot. I used this for income. Each income category originally included 11.1% (for sequential color scheme) or 10% (differential color scheme) of the data, however I rounded to the nearest $1000.

Sliding Percentile - I created this system to handle race because it has a large tail distribution. Ex. there are a lot of census tracts that have under 1% of several racial groups. If I use a percentile system then I will be creating category breaks for things like 0.3% vs 0.5%. So instead of having an equal percent of the data in each category, I weighted it so that the lowest categories have a larger percent of the data in them. For instance with 9 categories, I put in each category 22, 17, 15, 12, 10, 8, 7, 5, and 4 percent (instead of 11.1% in each). This allows us to show the differences between higher percents of a racial group that would otherwise be given the same color (ex. 30% vs 60%). I then rounded the categories to have nicer breaks (ex. to the nearest 0.5% or 1%).

Equal Breaks - This method would create categories with equal breaks. For instance for percent black the categories could be 0-20%, 20-40%, 40-60%, 60-80%, and 80%-100%. I used this for the race plural layer. I didn't use it elsewhere because it does a poor job of handling anything other than an even distribution.

Jenks Natural Breaks - This method minimizes the difference between each item in a category and the rest of items. I didn't use it because it gives too little emphasis to differences in the tail.


Color Schemes
Color schemes come from colorbrewer2.org.
Sequential - a continuum. All race layers use this as do two of the income layers.
Differential - emphasizes the break around the median value. Only used for one income layer.