rjd3highfreq
rjd3highfreq ships whatever the Java side ships, and only occasionally says what that was.
Comparison · Analytics
ggcorrplot vs n2kanalysis
A side-by-side editorial comparison of ggcorrplot and n2kanalysis — release velocity, themes, recent moves, and the top alternatives to consider.
ggcorrplot vs n2kanalysis: at a glance
What is ggcorrplot?
ggcorrplot came back after four years and found its significance markers had been lying
ggcorrplot draws correlation matrices in ggplot2 with optional significance marking and hierarchical reordering. It sat untouched from late 2022 until mid-2026, then shipped 0.2.0 and 0.3.0 sixteen days apart. Between them they added the display options users had been requesting since 2016 and repaired a set of bugs where hc.order = TRUE silently changed which cells were marked significant.
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.
ggcorrplot vs n2kanalysis: editorial side-by-side
ggcorrplot
2.5ANALYTICS
ggcorrplot came back after four years and found its significance markers had been lying
◆ Current state
ggcorrplot draws correlation matrices in ggplot2 with optional significance marking and hierarchical reordering. It sat untouched from late 2022 until mid-2026, then shipped 0.2.0 and 0.3.0 sixteen days apart. Between them they added the display options users had been requesting since 2016 and repaired a set of bugs where hc.order = TRUE silently changed which cells were marked significant.
◆ Where it's heading
Both releases chase the same target: parity with the older corrplot package inside a ggplot2 object. Significance stars appended to coefficient labels, circle scaling, decimal control, then boxed cells and glyphs sized by absolute correlation — these are corrplot's visual vocabulary reimplemented where they can be composed with other ggplot2 layers. The bug fixes point the other way, at foundations: p-values matched to cells by name rather than row position, clustering computed on the unrounded matrix, tl.col actually applied.
◆ Prediction
With the corrplot look largely reproduced and the correctness backlog cleared, the remaining gap is the mixed upper/lower display corrplot supports; that is the natural next argument if the current release pace holds.
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.
Alternatives to ggcorrplot and n2kanalysis
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 ggcorrplot or n2kanalysis.
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 ggcorrplot alternatives → · See all n2kanalysis alternatives →
Recent activity from ggcorrplot and n2kanalysis
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 21d agoggcorrplotggcorrplot 0.3.0 adds boxed cells and correlation-sized squares
- 1mo agoggcorrplotggcorrplot 0.2.0 fixes significance markers broken by hc.order
- 4mo agon2kanalysisconnect_inbo_s3() exposes temporary credentials to R
- 1y agon2kanalysisINLA models with SPDE elements supported
- 2y agon2kanalysisfit_model() made more efficient
- 3y agon2kanalysisHurdle models with imputation added
- 3y agoggcorrplotggcorrplot 0.1.4
- 6y agoggcorrplotggcorrplot 0.1.3
- 7y agoggcorrplotggcorrplot 0.1.2
- 7y agon2kanalysisImputed data handling improvements
- 7y agon2kanalysisINLA models consolidated onto a single class
- 10y agoggcorrplotggcorrplot's first release: correlograms in ggplot2
Frequently asked questions
What is the difference between ggcorrplot and n2kanalysis?
They serve adjacent needs but don't currently overlap on shipped themes. ggcorrplot 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 ggcorrplot better than n2kanalysis?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggcorrplot 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 ggcorrplot?
Top ggcorrplot alternatives in Analytics are ranked by recent ship velocity. Browse the "ggcorrplot alternatives" section above for the current picks, or visit /alternatives/ggcorrplot for the full list with editorial commentary on each.
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.