Lab 9 Bivariate Choropleth Mapping

The data for a bivariate map must be normalized like a regular choropleth map.  In this case obesity and physical inactivity are percentages of county population.  The data must then be broken into classes.  Choropleth maps with more than 9 classes are confusing and hard to read.  Data for this map was divided into 3 classes which produced a 9 class bivariate map.  Created by Ray Eslinger in Nassau County Fl.

Lab 8 Analytical Data

I incorporated what we learned this semester with color, typography, and balance to layout my infographic.  I chose two complementary colors purple and green for my two data frames.  I used color brewer to easily get similar saturation and lightness levels.  I chose green as the background color for the infographic and used my darkest purple from my obesity color ramp as the font color.  I placed the data frames with the obesity and diabetes levels in the center to establish the hierarchy.  To balance the infographic I placed supporting information to the sides.   I used the darkest purple and green from my color ramps for the chart colors.  I used a single sans serif font of various point sizes for the typography.  Created by Ray Eslinger in Nassau County Fl.

Lab 6 Choropleth Mapping

This lab had us making a choropleth map of population change in Georgia.  I first normalized the data by determining the percent of gain or loss for Georgia's County's populations. I then chose the complementary colors of purple and green to use with a diverging color ramp.  I created a basic legend showing the data classes created with natural breaks.  Created by Ray Eslinger in Nassau County Fl.