Multivariate spatio-temporal data have a spatial component referring to the location of each observation, a temporal component recorded at regular or irregular time intervals, and multiple variables measured at each spatial and temporal value. Often, such data are fragmented, reflecting a common practice of focusing on either spatial or temporal aspects separately. This fragmentation makes it difficult to handle them coherently and comprehensively. This work introduces a new data structure to facilitate the study of different portions or combinations of spatio-temporal data for exploratory data analysis. The proposed structure, implemented in the R package, cubble, organizes spatial and temporal variables as two facets of a single data object, allowing them to be wrangled separately or combined while ensuring synchronization. Examples will be provided to visualize weather station data with cubble using glyph maps.
Sherry Zhang
December 4, 2024