qqman
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
A side-by-side editorial comparison of climaemet and ggmagnify — release velocity, themes, recent moves, and the top alternatives to consider.
climaemet added weather alerts and wildfire risk, then spent two years managing rate limits.
climaemet wraps Spain's AEMET meteorological API — station data, historical climate series, forecasts, and the plotting helpers that go with them. Its capability surface widened decisively in 1.4.0 with meteorological alerts and wildfire risk rasters. Everything since has been about surviving the API rather than extending it: multiple API keys, quota-aware key selection, and httr2 throttling pinned to AEMET's stated 40-connections-per-minute policy.
A single-purpose ggplot2 inset tool, refining the same three arguments.
ggmagnify draws magnified insets of a region of a ggplot, with projection lines connecting the inset to its source area. The visible releases are all small refinements to how that inset looks — corner radius, fill between projection lines — plus one fix for inset themes being overridden. There are only three entries, so the picture is necessarily partial.
climaemet wraps Spain's AEMET meteorological API — station data, historical climate series, forecasts, and the plotting helpers that go with them. Its capability surface widened decisively in 1.4.0 with meteorological alerts and wildfire risk rasters. Everything since has been about surviving the API rather than extending it: multiple API keys, quota-aware key selection, and httr2 throttling pinned to AEMET's stated 40-connections-per-minute policy.
Two forces shape this package, and neither is feature demand. The first is AEMET's own churn — new response codes, a fires endpoint that switched to six risk levels returned as named factors, municipality datasets refreshed annually. The second is the maintainer's cross-package modernization, visible here as the API key store moving to tools::R_user_dir() with automatic migration, a configurable timeout, cli messaging, and an R 4.1 floor. The 1.6.0 refactor is stated as AI-assisted, matching the maintainer's other packages.
Expect the next release to track another AEMET endpoint change rather than add a data domain; the throttling and multi-key machinery suggests quota pressure is the constraint the maintainer keeps returning to.
ggmagnify draws magnified insets of a region of a ggplot, with projection lines connecting the inset to its source area. The visible releases are all small refinements to how that inset looks — corner radius, fill between projection lines — plus one fix for inset themes being overridden. There are only three entries, so the picture is necessarily partial.
Work concentrates on the visual finish of the inset rather than on new capability, which is what a package with one job should look like. Two feature releases a week apart in early 2024 suggest a short burst of attention rather than sustained development, and the feed goes quiet after mid-2024.
Too few entries to call a direction with confidence; continued small styling arguments would be consistent with what is visible.
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 climaemet or ggmagnify.
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 climaemet alternatives → · See all ggmagnify alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. climaemet and ggmagnify 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. climaemet and ggmagnify 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 climaemet alternatives in Analytics are ranked by recent ship velocity. Browse the "climaemet alternatives" section above for the current picks, or visit /alternatives/climaemet for the full list with editorial commentary on each.
Top ggmagnify alternatives in Analytics are ranked by recent ship velocity. Browse the "ggmagnify alternatives" section above for the current picks, or visit /alternatives/ggmagnify for the full list with editorial commentary on each.