A discussion of higher-dimension visualization of geographic clusters of voting patterns. Most visualizations are based on one dimensional (Democrat/Republican axis) or two-dimensional (correlation between two races, e.g. gap) relationships. It is possible to measure the "distance" between precincts in a higher dimensional space in terms of their voting patterns, where the distance is represented as sqrt( (candidate_a^2 + candidate_b^2 ...)/number of candidates)