The objective of the paper is to classify the labour markets of the EU member states on the basis of selected employment and unemployment indicators. In order to achieve the study target, the adequate multivariate exploration procedures have been chosen. In the first part of processing original data, principal component analysis (PCA) was employed. PCA is a multivariate statistical procedure used to reduce the number of observed variables into a smaller number of uncorrelated variables with a minimum loss of information. Moreover, the PCA results can be used for effective ranking of the EU countries according to observed indicators of labour markets. This paper describes the crucial steps in PCA and procedure for ranking mentioned and it reviews how PCA-based statistics are constructed and interpreted. The results of the study have demonstrated the range of application and advantages of the multivariate statistical approaches represented in this paper.