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dtplyr vs ggspatial

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

dtplyr vs ggspatial: at a glance

Featuredtplyrggspatial
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesdata.table, dplyr, translation, performancegeospatial, ggplot2, r-stats, terra-migration
Last editorial update3h ago49m ago
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What is dtplyr?

dtplyr stopped hijacking data.table objects and became an opt-in translator

dtplyr converts dplyr and tidyr code into data.table syntax, and 1.3.0 redrew its boundary: verbs no longer dispatch to dtplyr translations just because dtplyr is loaded, so lazy_dt() has to be called explicitly. Since then the work has been translation coverage — reframe(), case_match(), consecutive_id() — plus a long tail of correctness fixes in grouping and .by.

Read the full dtplyr trajectory →

What is ggspatial?

ggspatial finishes its move off raster and onto terra

ggspatial puts spatial data into ggplot2. Its recent history is a single multi-year migration: terra support arrived alongside raster in 1.1.6, and by 1.1.10 terra is the default in the bundled data loaders while raster is described as deprecated. Everything between those two releases is ggplot2 compatibility patching.

Read the full ggspatial trajectory →

dtplyr vs ggspatial: editorial side-by-side

D
dtplyr
ANALYTICS
0.0

dtplyr stopped hijacking data.table objects and became an opt-in translator

◆ Current state

dtplyr converts dplyr and tidyr code into data.table syntax, and 1.3.0 redrew its boundary: verbs no longer dispatch to dtplyr translations just because dtplyr is loaded, so lazy_dt() has to be called explicitly. Since then the work has been translation coverage — reframe(), case_match(), consecutive_id() — plus a long tail of correctness fixes in grouping and .by.

◆ Where it's heading

The package is trailing dplyr's own feature releases rather than leading them, adding each new verb once it settles upstream. Performance work is targeted at specific verbs where data.table has a faster primitive: setorder() for arrange(), reference drops for select(), rleid() for consecutive_id(). Release cadence has thinned considerably since 2023.

◆ Prediction

Expect further one-for-one translations as dplyr adds verbs, and continued fixes around .by and non-standard column names; the entries show no sign of a broader redesign.

G
ggspatial
ANALYTICS
0.0

ggspatial finishes its move off raster and onto terra

◆ Current state

ggspatial puts spatial data into ggplot2. Its recent history is a single multi-year migration: terra support arrived alongside raster in 1.1.6, and by 1.1.10 terra is the default in the bundled data loaders while raster is described as deprecated. Everything between those two releases is ggplot2 compatibility patching.

◆ Where it's heading

The package tracks the R spatial stack's own generational shift rather than setting direction itself — sf and stars support, then terra, then preparing S3 methods for the next ggplot2. Feature work is rare; the value it delivers is staying current with the layers underneath it.

◆ Prediction

The likely next step is completing the ggplot2 S3 method preparation that 1.1.10 started, with raster support eventually dropped rather than maintained in parallel.

Alternatives to dtplyr and ggspatial

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 dtplyr or ggspatial.

See all dtplyr alternatives → · See all ggspatial alternatives →

Recent activity from dtplyr and ggspatial

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

  1. 11mo agodtplyrreframe(), case_match() and consecutive_id() gain translations
  2. 11mo agoggspatialterra becomes the default raster backend
  3. 2y agoggspatialExample fixes for the updated raster/terra stack
  4. 3y agoggspatialannotation_spatial() fix for the latest ggplot2
  5. 3y agodtplyrcrayon dependency dropped
  6. 3y agodtplyrVerbs stop auto-dispatching; lazy_dt() now required
  7. 3y agoggspatialFix for behaviour deprecated in ggplot2
  8. 3y agoggspatialterra support, categorical rasters and better stars handling
  9. 3y agodtplyrdtplyr 1.2.2
  10. 4y agodtplyrdtplyr 1.2.1
  11. 4y agodtplyrEight tidyr verbs gain data.table translations
  12. 8y agoggspatialPackage size and CRAN check time reduced

Frequently asked questions

What is the difference between dtplyr and ggspatial?

They serve adjacent needs but don't currently overlap on shipped themes. dtplyr and ggspatial 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 dtplyr better than ggspatial?

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

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

What are the best alternatives to ggspatial?

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