STACAS
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
A side-by-side editorial comparison of rempsyc and soilDB — release velocity, themes, recent moves, and the top alternatives to consider.
Publication-ready psychology tables and plots, tracking APA style as closely as the software allows.
rempsyc produces APA-formatted tables and figures for psychology research — nice_table() for results tables, plus plotting helpers for scatter plots, violin plots, densities and simple slopes. Its releases are CRAN submissions that bundle a long run of development versions, so each entry reads as a digest rather than a single change. The most recent, 0.2.0, added point labelling and per-group correlation statistics to nice_scatter and fixed nice_lm() failing on factor covariates with more than two levels.
The R front door to USDA soil data finishes a long deprecation cleanup and turns local-first.
soilDB is the R access layer for USDA-NRCS soil data: NASIS local databases, Soil Data Access, SoilWeb coverage services, and a widening set of curated national grids. The 2.9.x line closed out a multi-release deprecation cycle — column aliases and stringsAsFactors are gone, R 4.1 is the floor, and the bundled sample profile collections were rebuilt against the new schema. Recent work has shifted from adding query functions to making existing ones faster and usable against local SQLite or GeoPackage copies.
rempsyc produces APA-formatted tables and figures for psychology research — nice_table() for results tables, plus plotting helpers for scatter plots, violin plots, densities and simple slopes. Its releases are CRAN submissions that bundle a long run of development versions, so each entry reads as a digest rather than a single change. The most recent, 0.2.0, added point labelling and per-group correlation statistics to nice_scatter and fixed nice_lm() failing on factor covariates with more than two levels.
Two forces drive this package and neither is its own roadmap. The first is APA style: when the 7th edition advised against beta for standardized coefficients, the package switched its output to italic b with an asterisk. The second is the surrounding ecosystem — formatting is aligned to what lavaanExtra and afex produce, contrast handling was delegated to easystats' modelbased, and Excel correlation matrix export was handed entirely to the correlation package to cut maintenance.
The pattern of delegating functionality to specialist packages while keeping the formatting layer is well established and likely continues. Because releases bundle many small dev versions, the next one will probably again mix plotting refinements with fixes surfaced by upstream changes.
soilDB is the R access layer for USDA-NRCS soil data: NASIS local databases, Soil Data Access, SoilWeb coverage services, and a widening set of curated national grids. The 2.9.x line closed out a multi-release deprecation cycle — column aliases and stringsAsFactors are gone, R 4.1 is the floor, and the bundled sample profile collections were rebuilt against the new schema. Recent work has shifted from adding query functions to making existing ones faster and usable against local SQLite or GeoPackage copies.
The arc points at offline and local-first workflows. downloadSSURGO() and createSSURGO() keep gaining arguments for building and querying local SSURGO databases, and the query internals were rewritten as common table expressions so identical code runs against the remote service or a local file. Coverage is widening in parallel: FY26 SoilWeb maps now reach most OCONUS surveys, while fetchHWSD() and fetchSOLUS() pull in datasets outside the core NASIS/SSURGO pair. Federal URL churn — EDIT, SoilWeb, S3-hosted geometry — is a recurring maintenance tax the package absorbs on users' behalf.
Expect the next releases to keep extending parallel and offline SSURGO handling, since LAPPLY.FUN has just opened the door to arbitrary parallel backends, and to fold more curated SoilWeb and FAO datasets behind fetch* wrappers.
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 rempsyc or soilDB.
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
A debugger for ggplot2's internals, hardening its grip as the internals it traces keep moving.
A univariate density estimator that added zero-inflated data and reopened its C++ API to do it.
Stationary vine copulas for time series, released in lockstep with the rest of Nagler's vine stack.
A single-purpose ggplot2 extension that has spent six years tracking ggplot2 instead of growing.
A Star Trek data package that became a Memory Alpha web client and has been patching scrapers ever since.
See all rempsyc alternatives → · See all soilDB alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. rempsyc and soilDB 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. rempsyc and soilDB 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.
Top rempsyc alternatives in Analytics are ranked by recent ship velocity. Browse the "rempsyc alternatives" section above for the current picks, or visit /alternatives/rempsyc for the full list with editorial commentary on each.
Top soilDB alternatives in Analytics are ranked by recent ship velocity. Browse the "soilDB alternatives" section above for the current picks, or visit /alternatives/soildb for the full list with editorial commentary on each.