micromapST: Exploring and Communicating Geospatial Patterns in US State Data

The linked micromap graphical design uses color to link each geographic unit’s name with its statistical graphic elements and map location across columns in a single row. Perceptual grouping of these rows into smaller chunks of data facilitates local focus and visual queries. Sorting the geographic units (the rows) in different ways can reveal patterns in the statistics, in the maps, and in the association between them. This design supports both exploration and communication in a multivariate geospatial context. This paper describes micromapST, an R package that implements the linked micromap graphical design specifically formatted for US state data, a common geographic unit used to display geographic patterns of health and other factors within the US. This package creates a graphic for the 51 geographic units (50 states plus DC) that fits on a single page, with states comprising the rows and state names, graphs and maps the columns. The graphical element for each state/column combination may represent a single statistical value, e.g., by a dot or horizontal bar, with or without an uncertainty measure. The distribution of values within each state, e.g., for counties, may be displayed by a boxplot. Two values per state may be represented by an arrow indicating the change in values, e.g., between two time points, or a scatter plot of the paired data. Categorical counts may be displayed as horizontal stacked bars, with optional standardization to percents or centering of the bars. Layout options include specification of the sort order for the rows, the graph/map linking colors, a vertical reference line and others. Output may be directed to the screen but is best displayed on a printer (or as a print image saved to any file format supported by R). The availability of a pre-defined linked micromap layout specifically for the 51 US states with graphical displays of single values, data distributions, change between two values, scatter plots of paired values, time series data and categorical data, facilitates quick exploration and communication of US state data for most common data types.