STACAS
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
A side-by-side editorial comparison of healthyR.ts and rnpn — release velocity, themes, recent moves, and the top alternatives to consider.
healthyR.ts keeps adding time-series helpers, then quietly breaks the old ones to modernise them.
A time-series companion in the healthyverse family, shipping helper functions in batches: growth-rate vectors, an ADF test and auto_stationarize() in 0.2.11, then five log and differencing transforms in 0.3.0, and a random-walk plot in 0.3.2. Alongside the additions runs a steady stream of breaking cleanups — invisible returns dropped, R 4.1 required for the native pipe, and ts_ma_plot() refactored onto ggplot2 facets with its xts output removed and its return value cut from six items to two.
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.
A time-series companion in the healthyverse family, shipping helper functions in batches: growth-rate vectors, an ADF test and auto_stationarize() in 0.2.11, then five log and differencing transforms in 0.3.0, and a random-walk plot in 0.3.2. Alongside the additions runs a steady stream of breaking cleanups — invisible returns dropped, R 4.1 required for the native pipe, and ts_ma_plot() refactored onto ggplot2 facets with its xts output removed and its return value cut from six items to two.
Two threads, both consistent. The functional one is coverage of the stationarity workflow — transform, test, auto-stationarize, plot — assembled function by function rather than as a single API. The structural one is convergence on ggplot2 and tidy conventions, retiring xts objects and multi-object return lists as it goes. The package is not afraid to break return shapes to get there, so upgrades are not drop-in.
Expect the remaining functions that still return xts objects or bundled lists to get the same ggplot2-only treatment, since ts_ma_plot() was refactored on exactly that rationale.
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 healthyR.ts 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.
See all healthyR.ts alternatives → · See all rnpn alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. healthyR.ts 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. healthyR.ts 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 healthyR.ts alternatives in Analytics are ranked by recent ship velocity. Browse the "healthyR.ts alternatives" section above for the current picks, or visit /alternatives/healthyr-ts 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.