STACAS
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
Comparison · Analytics
rnpn vs tbrf
A side-by-side editorial comparison of rnpn and tbrf — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
rnpn vs tbrf: at a glance
What is rnpn?
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.
What is tbrf?
Time-based rolling statistics for water-quality data, finally getting plotting and padding built in.
tbrf computes rolling statistics over time windows rather than fixed row counts — geometric means, confidence intervals and related summaries indexed by date. That distinction matters for irregularly sampled environmental monitoring data, where a fixed-width window spans different amounts of real time. Version 0.1.7 folds in stat_stepribbon() from ggalt, ships an Entero example dataset for lognormal workflows, and adds na.pad across the tbr_ family.
rnpn vs tbrf: editorial side-by-side
rnpn
0.0ANALYTICS
The USA phenology data client rebuilt its entire stack and stopped handing users -9999 as a number.
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
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.
tbrf
0.0ANALYTICS
Time-based rolling statistics for water-quality data, finally getting plotting and padding built in.
◆ Current state
tbrf computes rolling statistics over time windows rather than fixed row counts — geometric means, confidence intervals and related summaries indexed by date. That distinction matters for irregularly sampled environmental monitoring data, where a fixed-width window spans different amounts of real time. Version 0.1.7 folds in stat_stepribbon() from ggalt, ships an Entero example dataset for lognormal workflows, and adds na.pad across the tbr_ family.
◆ Where it's heading
The package spent its middle releases absorbing upstream breakage — a lubridate duration redefinition, a tibble 3.0.0 subassignment change, tidyselect internals. The 0.1.7 release breaks that pattern: it is the first in five years to add capability rather than repair it, and it does so by internalising a stat from an abandoned dependency instead of relying on it. Cadence remains very low, with a five-year gap between 0.1.5 and 0.1.6.
◆ Prediction
Absorbing stat_stepribbon() directly suggests further vendoring of the plotting layer rather than new statistical functions. The entries do not indicate which rolling statistics, if any, are queued next.
Alternatives to rnpn and tbrf
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 rnpn or tbrf.
ggtrace
A debugger for ggplot2's internals, hardening its grip as the internals it traces keep moving.
kde1d
A univariate density estimator that added zero-inflated data and reopened its C++ API to do it.
svines
Stationary vine copulas for time series, released in lockstep with the rest of Nagler's vine stack.
gghighlight
A single-purpose ggplot2 extension that has spent six years tracking ggplot2 instead of growing.
rtrek
A Star Trek data package that became a Memory Alpha web client and has been patching scrapers ever since.
Recent activity from rnpn and tbrf
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 11mo agornpnSentinel -9999 now converted to NA across all columns
- 0y agotbrfstat_stepribbon vendored in, plus na.pad on all rolling functions
- 1y agotbrfgm_mean_ci forwards na.rm and zero.propagate correctly
- 1y agornpnCustom season windows for phenometrics, and a speed regression fixed
- 1y agornpnDependency stack and return types replaced wholesale ⚡
- 1y agornpnBackfilled notes for seven earlier maintenance releases
- 6y agotbrfFix internals broken by tibble 3.0.0 subassignment
- 6y agotbrfDate windows recomputed with intervals and periods
Frequently asked questions
What is the difference between rnpn and tbrf?
Both compete on the same themes — r-package — within Analytics. rnpn and tbrf 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 rnpn better than tbrf?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. rnpn and tbrf 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 rnpn?
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.
What are the best alternatives to tbrf?
Top tbrf alternatives in Analytics are ranked by recent ship velocity. Browse the "tbrf alternatives" section above for the current picks, or visit /alternatives/tbrf for the full list with editorial commentary on each.