This chapter provides both a theoretical discussion of what multivariate exploratory approaches entail and step-by-step instructions to implement each of them with R. Four methods are presented: correspondence analysis, multiple correspondence analysis, principal component analysis, and exploratory factor analysis. These methods are designed to explore and summarize large and complex data tables by means of summary statistics. They help generate hypotheses by providing informative clusters using the variable values that characterize each observation.