← Back to home
Comparison · Analytics

gtsummary vs spatstat.geom

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

Shared themes:r-package

gtsummary vs spatstat.geom: at a glance

Featuregtsummaryspatstat.geom
SectorAnalyticsAnalytics
Velocity score0.02.5
Sparks · 30d00
Top themesclinical-tables, analysis-results-data, regression-summaries, reproducible-reportingspatial-statistics, computational-geometry, r-package, three-dimensional
Last editorial update1h ago5h ago
WebsiteVisit →Visit →

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 →

What is spatstat.geom?

The geometry layer under spatstat, steadily absorbing 3D patterns and missing-data semantics

spatstat.geom holds the spatial data structures and geometric operations the rest of the spatstat family builds on — windows, tessellations, images, point patterns and the operations that move between them. Recent releases split their attention between extending those structures to three dimensions and hardening the discretisation code where polygonal geometry meets a pixel grid. 3.8-2 adds more capabilities for three-dimensional point patterns.

Read the full spatstat.geom trajectory →

gtsummary vs spatstat.geom: editorial side-by-side

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.

S
spatstat.geom
ANALYTICS
2.5

The geometry layer under spatstat, steadily absorbing 3D patterns and missing-data semantics

◆ Current state

spatstat.geom holds the spatial data structures and geometric operations the rest of the spatstat family builds on — windows, tessellations, images, point patterns and the operations that move between them. Recent releases split their attention between extending those structures to three dimensions and hardening the discretisation code where polygonal geometry meets a pixel grid. 3.8-2 adds more capabilities for three-dimensional point patterns.

◆ Where it's heading

Two threads run through this window. The first is a family-wide push into 3D that originated in the simulation package and has now reached the geometry layer. The second is a slower semantic change: 3.5-0 introduced missing or unavailable (NA) spatial objects, and 3.6-0 followed with more facilities for handling them, meaning an absent window or image became a representable value rather than an error. Around both, the plotting and discretisation code accretes steadily — nonlinear colour maps, plot backgrounds, transparency control, signed distance transforms, and repeated attention to boundary pixels.

◆ Prediction

Expect the 3D surface here to keep filling in behind the simulation package rather than leading it, given that 3.8-2 follows the 3D simulation release by two months. The entries give no indication that the NA work is finished, since it has already spanned two releases.

Alternatives to gtsummary and spatstat.geom

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 gtsummary or spatstat.geom.

See all gtsummary alternatives → · See all spatstat.geom alternatives →

Recent activity from gtsummary and spatstat.geom

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

  1. 20d agospatstat.geomMore three-dimensional point pattern capabilities
  2. 2mo agospatstat.geomBetter boundary pixel handling when discretising windows
  3. 2mo agogtsummaryTheme elements no longer evaluated by default
  4. 6mo agospatstat.geomAnalytic level sets and signed distance transforms
  5. 8mo agogtsummaryARD strata functions and finer theme control
  6. 10mo agospatstat.geomNA object handling extended; clickpoly gains grid snapping
  7. 11mo agogtsummaryPer-level hierarchical sorting and labeled stacking
  8. 1y agospatstat.geomNA spatial objects, hole removal and connected components
  9. 1y agogtsummaryTable splitting, ID labeling, and add_difference_row
  10. 1y agospatstat.geomNonlinear colour and symbol maps; half-open quadrat tiles
  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 gtsummary and spatstat.geom?

Both compete on the same themes — r-package — within Analytics. spatstat.geom 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 gtsummary better than spatstat.geom?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. spatstat.geom 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 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.

What are the best alternatives to spatstat.geom?

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