rnaturalearth
rnaturalearth finished its sp exit and is now optimising how the data actually arrives.
Comparison · Analytics
esquisse vs see
A side-by-side editorial comparison of esquisse and see — release velocity, themes, recent moves, and the top alternatives to consider.
esquisse vs see: 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 see?
see grows wherever easystats adds a diagnostic, one plot method at a time.
see is the visualization layer for the easystats ecosystem, supplying plot() methods for performance, parameters and datawizard objects. Each release adds methods for whatever those packages shipped — prior predictive checks, DAG diagrams, factor-analysis graphs — alongside steady theme and geom refinement.
esquisse vs see: 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.
see
0.0ANALYTICS
see grows wherever easystats adds a diagnostic, one plot method at a time.
◆ Current state
see is the visualization layer for the easystats ecosystem, supplying plot() methods for performance, parameters and datawizard objects. Each release adds methods for whatever those packages shipped — prior predictive checks, DAG diagrams, factor-analysis graphs — alongside steady theme and geom refinement.
◆ Where it's heading
Growth here is downstream-driven rather than self-directed: see expands to cover new diagnostics as easystats produces them. Running alongside that is a sustained investment in presentation control — theme arguments on plot methods, elements that scale with base_size — which suits users embedding these plots in documents rather than glancing at them interactively.
◆ Prediction
Expect new plot methods to keep arriving in step with performance and parameters releases, with continued theming work rather than any change in the package's scope.
Alternatives to esquisse and see
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 see.
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 see alternatives →
Recent activity from esquisse and see
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agoseesee 0.14.1 adds plots for prior checks and grouped means
- 2mo agoseesee 0.14.0 renders factor loadings as node-edge graphs
- 6mo agoseesee 0.13.0 fixes reversed plot sorting, adds theme arguments
- 11mo agoseesee 0.12.0 extends normality checks to psych factor models
- 1y agoseesee 0.11.0 scales theme elements with base_size
- 1y agoseesee 0.10.0 plots random-effect group levels for mixed models
- 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 see?
They serve adjacent needs but don't currently overlap on shipped themes. esquisse and see 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 see?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. esquisse and see 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 see?
Top see alternatives in Analytics are ranked by recent ship velocity. Browse the "see alternatives" section above for the current picks, or visit /alternatives/see-r for the full list with editorial commentary on each.