Python and R house such data in “data frames.” A single table in a relational database would be an example of rectangular data, but typically multiple tables would have to be joined to obtain sufficient data for useful analysis. Text data, in its native form, is typically “unstructured” data, but can be converted to rectangular data in which each column is a word, each row is a document, and each cell entry is the frequency, or presence/absence, of that word in the document.
Rectangular data are the staple of statistical and machine learning models. Rectangular data are multivariate cross-sectional data (i.e. not time-series or repeated measure) in which each column is a variable (feature), and each row is a case or record.