rnaturalearth
rnaturalearth finished its sp exit and is now optimising how the data actually arrives.
Comparison · Analytics
esquisse vs modelbased
A side-by-side editorial comparison of esquisse and modelbased — release velocity, themes, recent moves, and the top alternatives to consider.
esquisse vs modelbased: at a glance
What is esquisse?
esquisse's 1.0 turned a point-and-click addin into embeddable Shiny modules.
The visible history covers the 1.0 line only. 1.0.0 is the substantial one: modules for importing data (via datamods) and exporting plots, a `ggplot_output()` / `render_ggplot()` pair, manual colour palettes, aesthetic parameter selection, more export formats including pptx, and typography controls. 1.0.1 and 1.0.2 are corrective — sf object handling, package-sourced data, disabled-panel label controls, and an `output_format` argument on the save modal.
What is modelbased?
modelbased is turning marginal effects into a full contrast grammar
modelbased computes marginal means, contrasts, and slopes from fitted models, and it ships every one to two months with a consistent shape: new comparison types, broader model support, and steady renaming toward clearer vocabulary. The recent arc runs from marginal effects inequality measures through inequality ratios to an omnibus global test and a post_process argument for multi-step comparisons. Argument names have been settled along the way, with trend becoming slope and an alias left behind.
esquisse vs modelbased: editorial side-by-side
esquisse
0.0ANALYTICS
esquisse's 1.0 turned a point-and-click addin into embeddable Shiny modules.
◆ Current state
The visible history covers the 1.0 line only. 1.0.0 is the substantial one: modules for importing data (via datamods) and exporting plots, a `ggplot_output()` / `render_ggplot()` pair, manual colour palettes, aesthetic parameter selection, more export formats including pptx, and typography controls. 1.0.1 and 1.0.2 are corrective — sf object handling, package-sourced data, disabled-panel label controls, and an `output_format` argument on the save modal.
◆ Where it's heading
The arc runs from a self-contained RStudio addin toward a component library other people build with: once plot rendering and export exist as Shiny modules, esquisse's ggplot builder can be dropped inside someone else's app rather than only launched beside RStudio. The two follow-up releases are consolidation on that surface rather than expansion of it.
◆ Prediction
Further work most likely lands on the module API and export coverage, since that is where 1.0.0 put the new surface and where 1.0.2 already returned. The entries do not indicate anything about cadence beyond this line.
modelbased
0.0ANALYTICS
modelbased is turning marginal effects into a full contrast grammar
◆ Current state
modelbased computes marginal means, contrasts, and slopes from fitted models, and it ships every one to two months with a consistent shape: new comparison types, broader model support, and steady renaming toward clearer vocabulary. The recent arc runs from marginal effects inequality measures through inequality ratios to an omnibus global test and a post_process argument for multi-step comparisons. Argument names have been settled along the way, with trend becoming slope and an alias left behind.
◆ Where it's heading
The package is building a compositional vocabulary rather than a fixed menu — contrasts of average slopes, contrasts across two numeric predictors, inequality summaries across all outcome categories, and now user-supplied post-processing of comparisons. Support quietly widens underneath, covering nestedLogit, brms finite mixtures, and offsets under population and average estimation. Plotting gets attention in proportion to how often these results are presented rather than tabulated, including collapse_by_group() for showing averaged raw data under mixed-model fits.
◆ Prediction
With post_process and omnibus tests both landed, the likely next step is making these composed comparisons easier to report — formatting or plotting methods for the multi-step results rather than new comparison types.
Alternatives to esquisse and modelbased
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 esquisse or modelbased.
writexl
writexl spent nine years refusing to do formatting, then shipped all of it in 2.0.0.
rgbif
rgbif is steadily pushing users off paged searching and onto real downloads.
rstanarm
rstanarm is community-maintained now, tracking Stan and lme4 rather than adding models.
taxa
taxa started a ground-up rewrite in 2021 and has published almost nothing since.
rotl
rotl's whole release history is keeping name matching honest against a moving taxonomy.
See all esquisse alternatives → · See all modelbased alternatives →
Recent activity from esquisse and modelbased
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agomodelbasedmodelbased 0.16.0 adds post-processing and omnibus contrast tests
- 3mo agomodelbasedmodelbased 0.15.0 contrasts average slopes across numeric predictors
- 5mo agomodelbasedmodelbased 0.14.0 renames trend to slope and adds collapse_by_group()
- 8mo agomodelbasedmodelbased 0.13.1 adds marginal group-level estimates and as.data.frame()
- 11mo agomodelbasedmodelbased 0.13.0 adds inequality ratios and slope marginalization
- 1y agomodelbasedmodelbased 0.12.0 introduces marginal effects inequality measures
- 5y agoesquisseesquisse v1.0.2
- 5y agoesquisseesquisse 1.0.1 fixes sf, package data and label controls
- 5y agoesquisseesquisse 1.0.0 ships embeddable plot and export modules ⚡
Frequently asked questions
What is the difference between esquisse and modelbased?
They serve adjacent needs but don't currently overlap on shipped themes. esquisse and modelbased 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.
Is esquisse better than modelbased?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. esquisse and modelbased 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.
What are the best alternatives to esquisse?
Top esquisse alternatives in Analytics are ranked by recent ship velocity. Browse the "esquisse alternatives" section above for the current picks, or visit /alternatives/esquisse for the full list with editorial commentary on each.
What are the best alternatives to modelbased?
Top modelbased alternatives in Analytics are ranked by recent ship velocity. Browse the "modelbased alternatives" section above for the current picks, or visit /alternatives/modelbased for the full list with editorial commentary on each.