← Back to home
Comparison · Analytics

gratia vs rnpn

A side-by-side editorial comparison of gratia and rnpn — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

gratia vs rnpn: at a glance

Featuregratiarnpn
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesgam, mgcv, ggplot2, statistical-graphicsphenology, api-client, ecological-data, data-cleaning
Last editorial update47m ago1h ago
WebsiteVisit →Visit →

What is gratia?

The tidy front-end for GAMs, now stable enough that upstream ggplot2 sets its release calendar.

gratia wraps mgcv-fitted generalized additive models in tidy data frames and ggplot2 graphics — smooth_estimates(), fitted_values(), derivatives(), draw() and appraise() cover evaluation, prediction and diagnostics. The API reached its intended shape at 0.9.0, when every generated column was renamed to a dot-prefixed form, and 0.10.0 added conditional_values() for covariate-conditional prediction plots.

Read the full gratia trajectory →

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.

Read the full rnpn trajectory →

gratia vs rnpn: editorial side-by-side

G
gratia
ANALYTICS
0.0

The tidy front-end for GAMs, now stable enough that upstream ggplot2 sets its release calendar.

◆ Current state

gratia wraps mgcv-fitted generalized additive models in tidy data frames and ggplot2 graphics — smooth_estimates(), fitted_values(), derivatives(), draw() and appraise() cover evaluation, prediction and diagnostics. The API reached its intended shape at 0.9.0, when every generated column was renamed to a dot-prefixed form, and 0.10.0 added conditional_values() for covariate-conditional prediction plots.

◆ Where it's heading

The package has moved through a long rewrite cycle and out the other side. Successive releases replaced evaluate_smooth() with smooth_estimates(), rebuilt draw() on top of it, then renamed the entire output vocabulary to avoid colliding with user variables. That work is finished; 0.11.1 is driven almost entirely by ggplot2 4.0.0 compatibility, with new mgcv family support for quantile residuals riding along. Development now tracks upstream breakage rather than internal redesign.

◆ Prediction

Expect the next releases to continue absorbing ggplot2 4.x and mgcv changes, with incremental family coverage in quantile_residuals() as the visible new work. The entries give no signal on which mgcv families come next.

R
rnpn
ANALYTICS
0.0

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.

Alternatives to gratia and rnpn

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 gratia or rnpn.

See all gratia alternatives → · See all rnpn alternatives →

Recent activity from gratia and rnpn

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 11mo agornpnSentinel -9999 now converted to NA across all columns
  2. 11mo agogratiaggplot2 4.0.0 compatibility, plus four more quantile-residual families
  3. 1y agornpnCustom season windows for phenometrics, and a speed regression fixed
  4. 1y agornpnDependency stack and return types replaced wholesale
  5. 1y agogratiaconditional_values() replaces vis.gam for conditional prediction plots
  6. 1y agornpnBackfilled notes for seven earlier maintenance releases
  7. 2y agogratiaparametric_effects() joins the dot-prefix rename; LSS families begin
  8. 2y agogratiaEvery generated column gains a dot prefix
  9. 3y agogratiaReal variable names in smooth_samples(), plus dplyr 1.1.0 fixes
  10. 4y agogratiaM1 example output fixes and confint tibble returns

Frequently asked questions

What is the difference between gratia and rnpn?

Both compete on the same themes — r-package — within Analytics. gratia 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.

Is gratia better than rnpn?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. gratia 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.

What are the best alternatives to gratia?

Top gratia alternatives in Analytics are ranked by recent ship velocity. Browse the "gratia alternatives" section above for the current picks, or visit /alternatives/gratia for the full list with editorial commentary on each.

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.