rjd3highfreq
rjd3highfreq ships whatever the Java side ships, and only occasionally says what that was.
Comparison · Analytics
n2kanalysis vs shapviz
A side-by-side editorial comparison of n2kanalysis and shapviz — release velocity, themes, recent moves, and the top alternatives to consider.
n2kanalysis vs shapviz: at a glance
What is n2kanalysis?
n2kanalysis has spent eight years wiring INLA models to an S3 bucket.
n2kanalysis is the analysis framework behind INBO's nature monitoring networks, wrapping INLA model fitting with a manifest-driven pipeline whose intermediate objects live in S3. Capability has arrived in discrete lumps: hurdle models with imputation and a manifest-to-bash converter in 0.3.1, SPDE spatial elements in INLA models in 0.4.0, and in 0.4.1 a connect_inbo_s3() function that makes temporary credentials available to the R functions.
What is shapviz?
shapviz refines its SHAP plots release by release while chasing ggplot2's moving target.
shapviz turns SHAP values from XGBoost, LightGBM, H2O, kernelshap and other sources into standard diagnostic plots — importance, dependence, waterfall, force and interaction. Recent work is plot ergonomics: shared y-axis control across dependence plots, a bar view for interaction values, and axis collection via patchwork. The two most recent releases are pure compatibility and bug fixes.
n2kanalysis vs shapviz: editorial side-by-side
n2kanalysis
0.0ANALYTICS
n2kanalysis has spent eight years wiring INLA models to an S3 bucket.
◆ Current state
n2kanalysis is the analysis framework behind INBO's nature monitoring networks, wrapping INLA model fitting with a manifest-driven pipeline whose intermediate objects live in S3. Capability has arrived in discrete lumps: hurdle models with imputation and a manifest-to-bash converter in 0.3.1, SPDE spatial elements in INLA models in 0.4.0, and in 0.4.1 a connect_inbo_s3() function that makes temporary credentials available to the R functions.
◆ Where it's heading
Development is slow, institutional, and driven by the modeling needs of specific monitoring programmes rather than a product roadmap. The pattern across the window is a new model class when the ecology requires one, then a stretch of infrastructure work around storage, credentials and pipeline efficiency. The 0.4.1 release is characteristic — a credentials helper, better result retrieval, more tests and a code-style pass, with no modeling change at all. Much of the early history is recorded only as merge-commit titles, so the release record thins out the further back it goes.
◆ Prediction
Expect the next substantive release to add another INLA model variant as a monitoring programme needs it, with S3 and credential handling continuing to absorb the maintenance effort in between.
shapviz
0.0ANALYTICS
shapviz refines its SHAP plots release by release while chasing ggplot2's moving target.
◆ Current state
shapviz turns SHAP values from XGBoost, LightGBM, H2O, kernelshap and other sources into standard diagnostic plots — importance, dependence, waterfall, force and interaction. Recent work is plot ergonomics: shared y-axis control across dependence plots, a bar view for interaction values, and axis collection via patchwork. The two most recent releases are pure compatibility and bug fixes.
◆ Where it's heading
Two threads run in parallel here. One is visual refinement converging on conventions from Python's shap — the 0.10.0 notes openly float switching share_y to TRUE to match it. The other is connector maintenance, keeping pace with H2O, XGBoost 1.x and 2.x, shapr and permshap as each changes. Neither thread adds new explanation methods; shapviz's job is presentation, and it is being polished rather than extended.
◆ Prediction
Expect share_y = TRUE to become the default and further ggplot2 4.x fallout, with connector updates arriving as the upstream SHAP packages release.
Alternatives to n2kanalysis and shapviz
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 n2kanalysis or shapviz.
audubon
audubon's release feed is almost entirely Renovate bumping the JavaScript toolchain behind its Japanese text splitter.
affiner
affiner is quietly turning a grid transformation helper into a small computational geometry library.
ageproR
ageproR spent two years chasing a moving file format, then added the recruitment models that justify the effort.
r-ledger
ledger adds a Rust toolchain fallback, so beancount imports work whether or not the Python tooling is installed.
gridpattern
gridpattern keeps widening its catalogue, and the newest patterns finally use the device's own line rendering.
See all n2kanalysis alternatives → · See all shapviz alternatives →
Recent activity from n2kanalysis and shapviz
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 4mo agon2kanalysisconnect_inbo_s3() exposes temporary credentials to R
- 10mo agoshapvizggplot 4.0 compatibility fix
- 1y agoshapvizFixes duplicated bars in sv_interaction()
- 1y agoshapvizggplot2 and patchwork dependency bumps
- 1y agoshapvizShared y-axis control and bar-style interaction plots
- 1y agon2kanalysisINLA models with SPDE elements supported
- 1y agoshapvizH2O random forests gain TreeSHAP support
- 1y agoshapvizFixes a broken vignette link
- 2y agon2kanalysisfit_model() made more efficient
- 3y agon2kanalysisHurdle models with imputation added
- 7y agon2kanalysisImputed data handling improvements
- 7y agon2kanalysisINLA models consolidated onto a single class
Frequently asked questions
What is the difference between n2kanalysis and shapviz?
They serve adjacent needs but don't currently overlap on shipped themes. n2kanalysis and shapviz 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 n2kanalysis better than shapviz?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. n2kanalysis and shapviz 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 n2kanalysis?
Top n2kanalysis alternatives in Analytics are ranked by recent ship velocity. Browse the "n2kanalysis alternatives" section above for the current picks, or visit /alternatives/n2kanalysis for the full list with editorial commentary on each.
What are the best alternatives to shapviz?
Top shapviz alternatives in Analytics are ranked by recent ship velocity. Browse the "shapviz alternatives" section above for the current picks, or visit /alternatives/shapviz for the full list with editorial commentary on each.