seriesgroups

Seriesgroups is a concept used in data analysis and visualization to organize multiple time series or sequential data sets into cohesive units. A seriesgroup consists of a collection of series that share a common context, such as measurement unit, geographic region, or experimental condition, enabling them to be plotted, compared, and analyzed together.

Structure and components: Each group has an identifier and a list of member series, along with optional shared properties such as axis mappings, color schemes, scale settings, and smoothing rules. Individual series retain their own data but can inherit or override group-level attributes to maintain visual and analytical consistency.

Operations and methods: Seriesgroups can be created by grouping a dataset on a chosen key, merged with other groups, or split into subgroups. Time alignment is a common task within a seriesgroup, using resampling, interpolation, or time zone normalization to ensure comparability. Within-group aggregation is also supported, including functions like mean, median, min, and max, applied across the member series.

Applications: The concept is applied in financial analytics to compare sectors, climate and environmental monitoring across locations, sensor networks, and clinical or experimental studies where results are tracked under common conditions. Visualization practices include overlaid plots, stacked representations, or faceted panels, all leveraging the shared context of a seriesgroup.

Implementation notes: In software libraries, a seriesgroup is typically represented as a container object holding series with shared visual and analytic properties. In data frames, group-by operations may yield a SeriesGroup structure or a facetting arrangement that guides rendering and analysis.

See also: time series, grouping, aggregation, faceting, multi-series charts.