qqman
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
Comparison · Analytics
constants vs ggsci
A side-by-side editorial comparison of constants and ggsci — release velocity, themes, recent moves, and the top alternatives to consider.
constants vs ggsci: at a glance
What is constants?
The R package for CODATA constants rebuilt its symbol table on NIST's naming so future updates stop being hand work.
constants exposes the CODATA recommended values of the physical constants to R, as a data frame plus symbol lists that carry units, uncertainties, or both. The package reached 1.0.0 on the 2018 CODATA release and has shipped once since, purely to track a units package update. Its surface is small and its release cadence is bound to CODATA, which revises every few years.
What is ggsci?
ggsci quietly became a palette mirror, then taught itself to generate colors on demand
ggsci ships ready-made ggplot2 color scales, originally journal and sci-fi palettes and now overwhelmingly terminal themes — the iTerm collection has grown past 400 entries and picks up 30 to 70 more with each sync. The one structural change in the recent run is gephi_palettes(), which generates distinct categorical colors for an arbitrary number of levels rather than serving a fixed list. Release cadence is steady, roughly every six to eight weeks.
constants vs ggsci: editorial side-by-side
constants
0.0ANALYTICS
The R package for CODATA constants rebuilt its symbol table on NIST's naming so future updates stop being hand work.
◆ Current state
constants exposes the CODATA recommended values of the physical constants to R, as a data frame plus symbol lists that carry units, uncertainties, or both. The package reached 1.0.0 on the 2018 CODATA release and has shipped once since, purely to track a units package update. Its surface is small and its release cadence is bound to CODATA, which revises every few years.
◆ Where it's heading
The direction set at 1.0.0 was to stop being a curated convenience wrapper and become a mechanical mirror of NIST. Hand-crafted symbol names were replaced with NIST's own ASCII symbols, categories adopted NIST's, and uncertainty switched from relative to absolute — all framed by the maintainer as necessary to make future CODATA updates routine. On top of that the package gained a correlation matrix and optional integration with the quantities package, moving it from a lookup table toward something that can propagate uncertainty.
◆ Prediction
Having rebuilt the symbol table specifically so CODATA revisions become mechanical, the next substantive release most likely tracks a new CODATA dataset rather than adding API. The experimental correlated-value support, disabled by default at 1.0.0, is the one part these entries flag as unfinished.
ggsci
2.5ANALYTICS
ggsci quietly became a palette mirror, then taught itself to generate colors on demand
◆ Current state
ggsci ships ready-made ggplot2 color scales, originally journal and sci-fi palettes and now overwhelmingly terminal themes — the iTerm collection has grown past 400 entries and picks up 30 to 70 more with each sync. The one structural change in the recent run is gephi_palettes(), which generates distinct categorical colors for an arbitrary number of levels rather than serving a fixed list. Release cadence is steady, roughly every six to eight weeks.
◆ Where it's heading
Two threads run in parallel. The larger one is curation: ggsci has effectively become a distribution channel for upstream color work, adding design-system palettes (Primer, Atlassian, Bootstrap, Tailwind) and re-syncing iTerm as that project changes, including correcting existing color values when upstream moves. The smaller and more interesting one is generation — the Gephi engine sidesteps the ceiling every fixed palette has, which is what happens when a plot needs more categories than any curated set provides.
◆ Prediction
Given how much of the release notes each cycle is a mechanical upstream sync, the plausible next step is automating those syncs rather than adding another vendor palette by hand; the Gephi generator is the more likely place any genuinely new capability appears.
Alternatives to constants and ggsci
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 constants or ggsci.
austraits
The R client for AusTraits spends its releases chasing the dataset it reads.
ggdemetra
A ggplot2 layer for seasonal adjustment output, filling in one plot type at a time.
fossilsim
A fossil-record simulator that quietly grew a trait-evolution engine.
tern.rbmi
Reference-based multiple imputation tables, shipping only what CRAN checks demand.
tern.mmrm
An MMRM tabulation package that has published nothing since its 2024 CRAN releases.
See all constants alternatives → · See all ggsci alternatives →
Recent activity from constants and ggsci
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 16d agoggsciggsci 5.2.0
- 1mo agoggsciggsci 5.1.0
- 4mo agoggsciggsci 5.0.0 generates categorical colors instead of serving a fixed list ⚡
- 4mo agoggsciggsci 4.3.0
- 8mo agoggsciggsci 4.2.0
- 9mo agoggsciggsci 4.1.0
- 5y agoconstantsCompatibility fix for units 0.7-0
- 5y agoconstantsconstants 1.0.0 ⚡
- 8y agoconstantsUnit handling fixes ahead of the 1.0.0 rebuild
Frequently asked questions
What is the difference between constants and ggsci?
They serve adjacent needs but don't currently overlap on shipped themes. ggsci is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is constants better than ggsci?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggsci is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
What are the best alternatives to constants?
Top constants alternatives in Analytics are ranked by recent ship velocity. Browse the "constants alternatives" section above for the current picks, or visit /alternatives/constants-r for the full list with editorial commentary on each.
What are the best alternatives to ggsci?
Top ggsci alternatives in Analytics are ranked by recent ship velocity. Browse the "ggsci alternatives" section above for the current picks, or visit /alternatives/ggsci for the full list with editorial commentary on each.