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ggsci vs gtsummary

A side-by-side editorial comparison of ggsci and gtsummary — release velocity, themes, recent moves, and the top alternatives to consider.

ggsci vs gtsummary: at a glance

Featureggscigtsummary
SectorAnalyticsAnalytics
Velocity score2.50.0
Sparks · 30d00
Top themescolor palettes, ggplot2, r, data visualizationclinical-tables, analysis-results-data, regression-summaries, reproducible-reporting
Last editorial update3h ago1h ago
WebsiteVisit →Visit →

What is ggsci?

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.

Read the full ggsci trajectory →

What is gtsummary?

gtsummary is quietly rebuilding itself around analysis results data, one table verb at a time.

gtsummary builds publication-ready summary, regression and survival tables for clinical and epidemiological work. Across this window it has grown in two directions at once: table composition primitives — splitting tables by rows and columns, stacking with labeled IDs, nested strata stacks, flexible merge columns — and a steadily deepening ARD layer, where tbl_ard_* functions, gather_ard() and the hierarchical table family expose the underlying analysis results data as a first-class object.

Read the full gtsummary trajectory →

ggsci vs gtsummary: editorial side-by-side

G
ggsci
ANALYTICS
2.5

ggsci quietly became a palette mirror, then taught itself to generate colors on demand

◆ Current state

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.

◆ Where it's heading

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.

◆ Prediction

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.

G
gtsummary
ANALYTICS
0.0

gtsummary is quietly rebuilding itself around analysis results data, one table verb at a time.

◆ Current state

gtsummary builds publication-ready summary, regression and survival tables for clinical and epidemiological work. Across this window it has grown in two directions at once: table composition primitives — splitting tables by rows and columns, stacking with labeled IDs, nested strata stacks, flexible merge columns — and a steadily deepening ARD layer, where tbl_ard_* functions, gather_ard() and the hierarchical table family expose the underlying analysis results data as a first-class object.

◆ Where it's heading

The ARD work is the through-line. Table IDs exist so gather_ard() can return a named list; hierarchical tables gained per-level sorting and targeted filtering; ARD inputs are pre-processed so sorting applies to non-standard shapes. The package is becoming a structured-results engine that happens to render tables, rather than a renderer alone. Alongside that, 2.2.0 restored data pre-processing that 2.0 had removed after the reduced functionality hurt users — a maintainer willing to reverse a major-version decision.

◆ Prediction

Expect the hierarchical and ARD functions, introduced as a preview without a full deprecation cycle, to keep stabilizing toward a settled API rather than new table types appearing.

Alternatives to ggsci and gtsummary

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 ggsci or gtsummary.

See all ggsci alternatives → · See all gtsummary alternatives →

Recent activity from ggsci and gtsummary

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 15d agoggsciggsci 5.2.0
  2. 1mo agoggsciggsci 5.1.0
  3. 2mo agogtsummaryTheme elements no longer evaluated by default
  4. 4mo agoggsciggsci 5.0.0 generates categorical colors instead of serving a fixed list
  5. 4mo agoggsciggsci 4.3.0
  6. 8mo agoggsciggsci 4.2.0
  7. 8mo agogtsummaryARD strata functions and finer theme control
  8. 9mo agoggsciggsci 4.1.0
  9. 11mo agogtsummaryPer-level hierarchical sorting and labeled stacking
  10. 1y agogtsummaryTable splitting, ID labeling, and add_difference_row
  11. 1y agogtsummaryData pre-processing restored after the 2.0 removal
  12. 1y agogtsummarytbl_merge gains explicit merge columns

Frequently asked questions

What is the difference between ggsci and gtsummary?

They serve adjacent needs but don't currently overlap on shipped themes. 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.

Is ggsci better than gtsummary?

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.

What are the best alternatives to ggsci?

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.

What are the best alternatives to gtsummary?

Top gtsummary alternatives in Analytics are ranked by recent ship velocity. Browse the "gtsummary alternatives" section above for the current picks, or visit /alternatives/gtsummary-r for the full list with editorial commentary on each.