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ggmapinset vs rnpn

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

ggmapinset vs rnpn: at a glance

Featureggmapinsetrnpn
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesggplot2, geospatial, inset-maps, extension-apiphenology, api-client, ecological-data, data-cleaning
Last editorial update3h ago1h ago
WebsiteVisit →Visit →

What is ggmapinset?

A ggplot2 inset-map extension that is now infrastructure for other packages

ggmapinset adds magnified inset panels to ggplot2 sf maps, handling the coordinate transformation, the inset frame and the sf-related stat layers that have to follow it. The 0.5.0 release is aimed less at end users than at extension authors: coerce_centre() is a new extension point required by sibling package ggautomap, and the inset parameter drops NA in favour of waiver() as its default. It comes from cidm-ph, alongside nswgeo.

Read the full ggmapinset 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 →

ggmapinset vs rnpn: editorial side-by-side

G
ggmapinset
ANALYTICS
0.0

A ggplot2 inset-map extension that is now infrastructure for other packages

◆ Current state

ggmapinset adds magnified inset panels to ggplot2 sf maps, handling the coordinate transformation, the inset frame and the sf-related stat layers that have to follow it. The 0.5.0 release is aimed less at end users than at extension authors: coerce_centre() is a new extension point required by sibling package ggautomap, and the inset parameter drops NA in favour of waiver() as its default. It comes from cidm-ph, alongside nswgeo.

◆ Where it's heading

The package has moved steadily from feature to foundation. 0.3.0 replaced confusing parameter names and rebuilt everything on stat_sf_inset() so coordinate limits stayed correct, then exposed transform_to_inset() explicitly for extension developers. 0.4.0 generalised inset shapes beyond circles to rectangles and arbitrary sf geometries. 0.5.0 continues in that direction, changing defaults in ways that require downstream extensions to adapt — the cost of being depended upon.

◆ Prediction

Expect further extension points driven by what ggautomap and the other cidm-ph mapping packages need, with the user-facing inset API staying largely settled after the shape generalisation.

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 ggmapinset 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 ggmapinset or rnpn.

See all ggmapinset alternatives → · See all rnpn alternatives →

Recent activity from ggmapinset and rnpn

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

  1. 4mo agoggmapinsetNew extension point for ggautomap; waiver() replaces NA
  2. 11mo agornpnSentinel -9999 now converted to NA across all columns
  3. 1y agornpnCustom season windows for phenometrics, and a speed regression fixed
  4. 1y agornpnDependency stack and return types replaced wholesale
  5. 1y agoggmapinsetRectangular and arbitrary sf inset shapes
  6. 1y agornpnBackfilled notes for seven earlier maintenance releases
  7. 3y agoggmapinsetRebuilt on stat_sf_inset() with corrected coordinate limits

Frequently asked questions

What is the difference between ggmapinset and rnpn?

They serve adjacent needs but don't currently overlap on shipped themes. ggmapinset 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 ggmapinset better than rnpn?

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

Top ggmapinset alternatives in Analytics are ranked by recent ship velocity. Browse the "ggmapinset alternatives" section above for the current picks, or visit /alternatives/ggmapinset 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.