qqman
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
A side-by-side editorial comparison of quantities and tmap — release velocity, themes, recent moves, and the top alternatives to consider.
The glue package that makes R carry units and uncertainty through the same calculation.
quantities combines the units and errors packages into one class so values keep both their measurement units and their uncertainty through arithmetic, subsetting and data frame operations. Recent releases have been narrow: fixes to the covariance and correlation implementations, and performance work on the data.frame methods. Most of the release traffic is coordination with its two parent packages.
Two years after a from-scratch rewrite, tmap is filling in the layers v4 promised.
tmap draws thematic maps in R across static and interactive modes. The 4.0 rewrite replaced the layer syntax with explicit visual variables, scales, legends and charts, and opened the package to extensions; the 4.x line since has been steady capability fill-in. The 4.4 release adds tm_circles with fixed unit-based radii, a blend argument on every layer, and hitboxes so small objects stay clickable in view mode.
quantities combines the units and errors packages into one class so values keep both their measurement units and their uncertainty through arithmetic, subsetting and data frame operations. Recent releases have been narrow: fixes to the covariance and correlation implementations, and performance work on the data.frame methods. Most of the release traffic is coordination with its two parent packages.
The design settled with 0.2.0, which made uncertainty unit-aware and added correlation and covariance support for quantities objects. Since then the package behaves like the integration layer it is — releasing when units, errors, dplyr or ggplot2 shift underneath it rather than on its own schedule. Several releases consist only of test repairs against upstream changes.
Expect the next release to follow a units or errors change rather than introduce new behaviour of its own.
tmap draws thematic maps in R across static and interactive modes. The 4.0 rewrite replaced the layer syntax with explicit visual variables, scales, legends and charts, and opened the package to extensions; the 4.x line since has been steady capability fill-in. The 4.4 release adds tm_circles with fixed unit-based radii, a blend argument on every layer, and hitboxes so small objects stay clickable in view mode.
The extension mechanism introduced in 4.0 is where the interesting work is migrating: PMTiles support arrived through a separate experimental tmap.sources package, mode cycling became configurable via tmap_mode_pool() so packages like tmap.mapgl can register themselves, and shiny dispatch methods were added specifically to let other modes integrate. The core package is increasingly a rendering contract that satellite packages plug into.
Expect more rendering backends to land as sibling packages rather than in tmap itself, with the core continuing to absorb the dispatch and mode-management plumbing they need.
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 quantities or tmap.
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
The R package for CODATA constants rebuilt its symbol table on NIST's naming so future updates stop being hand work.
The R client for AusTraits spends its releases chasing the dataset it reads.
A ggplot2 layer for seasonal adjustment output, filling in one plot type at a time.
A fossil-record simulator that quietly grew a trait-evolution engine.
Reference-based multiple imputation tables, shipping only what CRAN checks demand.
See all quantities alternatives → · See all tmap alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. quantities and tmap 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. quantities and tmap 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 quantities alternatives in Analytics are ranked by recent ship velocity. Browse the "quantities alternatives" section above for the current picks, or visit /alternatives/quantities for the full list with editorial commentary on each.
Top tmap alternatives in Analytics are ranked by recent ship velocity. Browse the "tmap alternatives" section above for the current picks, or visit /alternatives/tmap-r for the full list with editorial commentary on each.