Apartment characteristics including prices, internal attributes and location attributes consisting of travel times to urban centres and income variables are analysed with exploratory factor analysis. Principal axis factoring with oblique rotation is applied, which allows the extracted factors to be correlated. Four factors are extracted, of which two represent apartment attributes and other two ñ location attributes. The analysed area is the French adjacent cities of Lyon and Villeurbanne. Spatial distribution of the factors provides an insight into both apartment attributes and urban structure. In particular, factors show the concentration of big expensive apartments on the one hand and older apartments in bad condition on the other; they also demonstrate a contradiction with the existing city boundaries in the north and highlight the existence of a problematic low income area in the central part of Lyon. Principal component analysis is applied for a more comprehensive study of location attributes. The clusters of components obtained by K-means algorithm are seen as proxies for apartment submarkets, which are useful for a subsequent study.