Categorizing a City Using Cluster Analysis
K-means cluster analysis identifying spatial autocorrelation among block-group socioeconomic indicators
To identify potential spatial autocorrelation among socioeconomic indicators at the block-group level, this project runs a k-means cluster analysis to determine the optimal number of block-group clusters within the city.