STACAS
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
A side-by-side editorial comparison of eulerr and rnpn — release velocity, themes, recent moves, and the top alternatives to consider.
The area-proportional Euler diagram package is finished software, and maintained like it.
eulerr generates area-proportional Euler and Venn diagrams by numerically optimizing shape positions and sizes to match set relationships, with the fitting done in C++. The last feature release was 7.0.0 in December 2022, which made the optimization's loss function user-selectable. Everything since has been maintenance: documentation URL corrections, a strip-layout fix when grouping, an Armadillo deprecation, and an R CMD check warning about an unignored config file.
The USA phenology data client rebuilt its entire stack and stopped handing users -9999 as a number.
rnpn is the R client for the USA National Phenology Network, retrieving observation records, phenometrics and gridded model layers. Version 1.3.0 in March 2025 replaced nearly all of its infrastructure at once — sp and raster dropped, terra made optional, XML swapped for xml2, plyr for dplyr, httr and curl for httr2 — and changed what functions return, with tibbles in place of data.tables and empty tibbles in place of NULL on error. The two releases since have completed the missing-value handling and restored performance lost in the transition.
eulerr generates area-proportional Euler and Venn diagrams by numerically optimizing shape positions and sizes to match set relationships, with the fitting done in C++. The last feature release was 7.0.0 in December 2022, which made the optimization's loss function user-selectable. Everything since has been maintenance: documentation URL corrections, a strip-layout fix when grouping, an Armadillo deprecation, and an R CMD check warning about an unignored config file.
This is a mature package whose problem is solved, and the release pattern reflects that — three of the last four releases changed nothing a user would see. What activity remains is tracking its dependencies rather than its own roadmap: keeping up with Armadillo's deprecations and R CMD check policy is the whole of recent work. The two September 2025 releases an hour apart are a fix and its follow-up, not a development cycle restarting.
The pattern points to continued upkeep triggered by upstream C++ and CRAN check changes rather than new capability. If anything does move, the configurable loss function added in 7.0.0 is the surface with room left in it.
rnpn is the R client for the USA National Phenology Network, retrieving observation records, phenometrics and gridded model layers. Version 1.3.0 in March 2025 replaced nearly all of its infrastructure at once — sp and raster dropped, terra made optional, XML swapped for xml2, plyr for dplyr, httr and curl for httr2 — and changed what functions return, with tibbles in place of data.tables and empty tibbles in place of NULL on error. The two releases since have completed the missing-value handling and restored performance lost in the transition.
The package is being brought onto the current R stack and made honest about missing data, and those are the same project. Converting the -9999 sentinel to NA started in 1.3.0 for download functions and was extended to all columns in 1.4.1; the string "emptyvalue" got the same treatment. Beyond the migration, the feature additions are modest and specific to the domain, such as custom start and end dates for defining a phenometrics season.
With the dependency migration finished and sentinel handling now applied across all columns, the next releases most likely return to domain features and to fixes surfaced by the server side, which has already prompted work through migrations and backend moves. The removed progress indicator is an acknowledged regression that may come back.
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 eulerr or rnpn.
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.
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. eulerr and rnpn 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. eulerr and rnpn 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 eulerr alternatives in Analytics are ranked by recent ship velocity. Browse the "eulerr alternatives" section above for the current picks, or visit /alternatives/eulerr for the full list with editorial commentary on each.
Top rnpn alternatives in Analytics are ranked by recent ship velocity. Browse the "rnpn alternatives" section above for the current picks, or visit /alternatives/rnpn for the full list with editorial commentary on each.