In the next three blog posts, basic Geo-spatial analysis in R using publicly available data will be performed. This is commonly used to show a correlation between location and potential patient related issues. In the next three post, US census data will be used to show:

• Part 1: Basic 2D Geo-spatial using census data along with the ggpubr package to combine the different plots.
• Part 2: Conversion of 2D plots into a pseudo-3D projection using a shear matrix * rotation matrix + shift X,Y matrix. This modifies a function written by Junger and Cohen to allow for custom theta (rotation angle) and shear matrix.
• Part 3: Use of a basic bi variate color scheme to concurrently display two variables on one GIS map.

These are basic examples using US Census data but are commonly can be used to look for geographical “hot spots” of disease similar to the classic “Snow Cholera Plot”.