n2kanalysis
n2kanalysis has spent eight years wiring INLA models to an S3 bucket.
A side-by-side editorial comparison of dggridR and ggstatsplot — release velocity, themes, recent moves, and the top alternatives to consider.
A discrete global grid generator grew cell traversal and became a usable spatial index.
dggridR builds discrete global grids — icosahedral tessellations of the Earth into equal-area hexagonal or triangular cells — by wrapping the DGGRID C++ engine. The 4.1.0 release adds dgneighbors, dgchildren and dgparent for moving between adjacent cells and across resolutions, plus dgpoints_to_cells and dgbin_points for mapping and aggregating point data into cells. New aperture 7 and mixed-aperture ISEA43H grid types arrive alongside them.
ggstatsplot reached 1.0 by adding tests, having outsourced its statistics years ago.
ggstatsplot produces ggplot2 graphics with statistical test results embedded in the subtitle and caption — comparisons, correlations, contingency tables, histograms. Since the 2019 refactoring that moved all statistical computation into the separate statsExpressions package, its own release notes have been dominated by upstream tracking: adapting to ggplot2, dplyr, purrr and easystats changes. The 1.0.0 release in April 2026 breaks that run with real additions to the contingency-table functions.
dggridR builds discrete global grids — icosahedral tessellations of the Earth into equal-area hexagonal or triangular cells — by wrapping the DGGRID C++ engine. The 4.1.0 release adds dgneighbors, dgchildren and dgparent for moving between adjacent cells and across resolutions, plus dgpoints_to_cells and dgbin_points for mapping and aggregating point data into cells. New aperture 7 and mixed-aperture ISEA43H grid types arrive alongside them.
The package changed hands in effect as well as in code: the 4.0.0 engine update to DGGRID v9.0b and the first real test suite were contributed by Sebastian Krantz, who also maintains the upstream engine fork, and 4.1.0's feature burst followed two weeks later. The direction of that burst is unmistakable — away from generating grids for plotting and toward using them as an indexing structure that point data gets binned into and navigated through.
Expect the cell hierarchy functions to extend to non-hexagonal apertures and multi-level traversal, closing the remaining gaps against established global indexing systems.
ggstatsplot produces ggplot2 graphics with statistical test results embedded in the subtitle and caption — comparisons, correlations, contingency tables, histograms. Since the 2019 refactoring that moved all statistical computation into the separate statsExpressions package, its own release notes have been dominated by upstream tracking: adapting to ggplot2, dplyr, purrr and easystats changes. The 1.0.0 release in April 2026 breaks that run with real additions to the contingency-table functions.
The architecture explains the cadence. With statistics living in statsExpressions, ggstatsplot's own releases are mostly the tax of sitting on top of a fast-moving plotting and tidyverse stack — five of the six most recent entries change nothing a user would notice. When substantive work does arrive it clusters in the plotting layer's coverage of test families, as in 1.0.0's one-sample goodness-of-fit support and pairwise contingency analyses. The maintainer is also visibly deliberate about scope, having removed the normality-curve overlay in 0.12.4 for being unrelated to the analysis in question.
Expect continued parity work across the plot family — features that exist in one function being extended to its siblings, as goodness-of-fit support moved from ggpiestats to ggbarstats — punctuated by maintenance releases tracking ggplot2 and easystats.
Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either dggridR or ggstatsplot.
n2kanalysis has spent eight years wiring INLA models to an S3 bucket.
A Fortran-descended optimizer got thread-safe, then found two flags that never worked.
collapse got a JSS paper and a 7x fmean speedup in the same release.
gtsummary is quietly rebuilding itself around analysis results data, one table verb at a time.
broadcast is filling in NumPy-style array broadcasting for R, operator by operator.
climaemet added weather alerts and wildfire risk, then spent two years managing rate limits.
See all dggridR alternatives → · See all ggstatsplot alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. dggridR and ggstatsplot are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. dggridR and ggstatsplot are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
Top dggridR alternatives in Analytics are ranked by recent ship velocity. Browse the "dggridR alternatives" section above for the current picks, or visit /alternatives/dggridr for the full list with editorial commentary on each.
Top ggstatsplot alternatives in Analytics are ranked by recent ship velocity. Browse the "ggstatsplot alternatives" section above for the current picks, or visit /alternatives/ggstatsplot for the full list with editorial commentary on each.