Using various software packages and statistical techniques, this paper will explore the spatial relationships of affordable housing programs in Philadelphia including housing supported by public housing programs, community development corporations, and nonprofit organizations. ArcView GIS, ArcView 3D Analyst, ArcView Spatial Analyst, S-Plus for ArcView GIS, and MATLAB will be used to consider the relationship of affordable housing to neighborhood characteristics as well as clustering patterns and "hot spots." The role of GIS in evaluating the impact of programs and forming public policy will be explored. Specific exploratory spatial data analysis (ESDA) techniques to be used include K functions, tests for spatial autocorrelation, and spatial regression.