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The Manhattan-plot package for GWAS results, finished and dormant since 2017.
A side-by-side editorial comparison of ggdemetra and ggsci — release velocity, themes, recent moves, and the top alternatives to consider.
A ggplot2 layer for seasonal adjustment output, filling in one plot type at a time.
ggdemetra is a thin, focused bridge: it puts RJDemetra's seasonal adjustment results — TRAMO-SEATS and X-13 models — into ggplot2 geoms and autoplot methods. Development runs in short bursts separated by long quiet stretches, and the most recent work has been correcting SI ratio handling rather than adding surface. The API is small enough that a single function rename counts as the notable change in a release.
ggsci quietly became a palette mirror, then taught itself to generate colors on demand
ggsci ships ready-made ggplot2 color scales, originally journal and sci-fi palettes and now overwhelmingly terminal themes — the iTerm collection has grown past 400 entries and picks up 30 to 70 more with each sync. The one structural change in the recent run is gephi_palettes(), which generates distinct categorical colors for an arbitrary number of levels rather than serving a fixed list. Release cadence is steady, roughly every six to eight weeks.
ggdemetra is a thin, focused bridge: it puts RJDemetra's seasonal adjustment results — TRAMO-SEATS and X-13 models — into ggplot2 geoms and autoplot methods. Development runs in short bursts separated by long quiet stretches, and the most recent work has been correcting SI ratio handling rather than adding surface. The API is small enough that a single function rename counts as the notable change in a release.
The package has been steadily completing its coverage of the seasonal adjustment output surface: component extractors and autoplot methods in 0.2.3, SI ratio plotting in 0.2.5, then two releases of corrections to make SI ratios behave under TRAMO-SEATS jSA models and when no seasonal component is exported. Alongside that, the naming is being tidied — y_forecast() became raw(), and init_ggplot() shortened the setup boilerplate. This reads as a package approaching the edge of its intended scope and spending its effort on correctness.
Two consecutive releases fixing SI ratios under TRAMO-SEATS suggest that code path is the least settled part of the package, so further corrections there are the most likely next move. The entries give no indication of new model families or plot types being planned.
ggsci ships ready-made ggplot2 color scales, originally journal and sci-fi palettes and now overwhelmingly terminal themes — the iTerm collection has grown past 400 entries and picks up 30 to 70 more with each sync. The one structural change in the recent run is gephi_palettes(), which generates distinct categorical colors for an arbitrary number of levels rather than serving a fixed list. Release cadence is steady, roughly every six to eight weeks.
Two threads run in parallel. The larger one is curation: ggsci has effectively become a distribution channel for upstream color work, adding design-system palettes (Primer, Atlassian, Bootstrap, Tailwind) and re-syncing iTerm as that project changes, including correcting existing color values when upstream moves. The smaller and more interesting one is generation — the Gephi engine sidesteps the ceiling every fixed palette has, which is what happens when a plot needs more categories than any curated set provides.
Given how much of the release notes each cycle is a mechanical upstream sync, the plausible next step is automating those syncs rather than adding another vendor palette by hand; the Gephi generator is the more likely place any genuinely new capability appears.
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 ggdemetra or ggsci.
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
The R package for CODATA constants rebuilt its symbol table on NIST's naming so future updates stop being hand work.
The R client for AusTraits spends its releases chasing the dataset it reads.
A fossil-record simulator that quietly grew a trait-evolution engine.
Reference-based multiple imputation tables, shipping only what CRAN checks demand.
An MMRM tabulation package that has published nothing since its 2024 CRAN releases.
See all ggdemetra alternatives → · See all ggsci alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — ggplot2 — within Analytics. ggsci is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. 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. ggsci is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
Top ggdemetra alternatives in Analytics are ranked by recent ship velocity. Browse the "ggdemetra alternatives" section above for the current picks, or visit /alternatives/ggdemetra for the full list with editorial commentary on each.
Top ggsci alternatives in Analytics are ranked by recent ship velocity. Browse the "ggsci alternatives" section above for the current picks, or visit /alternatives/ggsci for the full list with editorial commentary on each.