qqman
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
A side-by-side editorial comparison of inbospatial and quantities — release velocity, themes, recent moves, and the top alternatives to consider.
A thin R wrapper over Flemish geospatial services, adding one standard at a time
inbospatial gives R users direct access to Flemish and Belgian government spatial services without hand-writing request URLs. Three releases over three years have built it up service by service: WMS and WMTS tile shorthands and projection-distortion utilities first, then the Flanders digital elevation model, and now OGC API Features querying plus layer discovery for WCS services. Much of each release is hardening the MHT-file parsing that these services return.
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.
inbospatial gives R users direct access to Flemish and Belgian government spatial services without hand-writing request URLs. Three releases over three years have built it up service by service: WMS and WMTS tile shorthands and projection-distortion utilities first, then the Flanders digital elevation model, and now OGC API Features querying plus layer discovery for WCS services. Much of each release is hardening the MHT-file parsing that these services return.
The package grows by absorbing one more service standard per release rather than by adding abstraction. The 0.1.0 additions point the same way — get_feature_ogc() covers a newer OGC standard alongside the existing WCS and WFS paths, and get_wcs_layers() addresses the practical problem that you cannot query a coverage without first knowing what layers exist. Release cadence is slow and driven by which service the maintainers needed next.
Expect the next release to add another regional service endpoint or extend OGC API Features coverage, on a timescale of a year or more given the gaps between the three releases so far.
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.
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 inbospatial or quantities.
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 inbospatial alternatives → · See all quantities alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. inbospatial and quantities 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. inbospatial and quantities 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 inbospatial alternatives in Analytics are ranked by recent ship velocity. Browse the "inbospatial alternatives" section above for the current picks, or visit /alternatives/inbospatial for the full list with editorial commentary on each.
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.