qqman
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
A side-by-side editorial comparison of constants and tidypolars — release velocity, themes, recent moves, and the top alternatives to consider.
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.
tidypolars is grinding toward complete dplyr coverage, one supported function at a time
tidypolars lets you write dplyr and tidyr syntax against Polars DataFrames and LazyFrames. Its releases follow a fixed shape: raise the required polars version, add a handful of newly supported R functions and arguments, fix places where behaviour diverges from dplyr. Recent additions run from %notin% and as.integer() to .before/.after in mutate() and time zone handling in datetime parsing. Cadence is roughly every six to ten weeks and has not varied.
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.
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.
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.
tidypolars lets you write dplyr and tidyr syntax against Polars DataFrames and LazyFrames. Its releases follow a fixed shape: raise the required polars version, add a handful of newly supported R functions and arguments, fix places where behaviour diverges from dplyr. Recent additions run from %notin% and as.integer() to .before/.after in mutate() and time zone handling in datetime parsing. Cadence is roughly every six to ten weeks and has not varied.
Coverage is the whole strategy, and the target has been widening from dplyr into tidyr — unnest_longer_polars(), separate_longer_delim_polars() and separate_longer_position_polars() bring list-column and string-splitting verbs that have no Polars-idiomatic equivalent in the tidyverse dialect. The other consistent thread is fidelity: distinct() dropping unselected columns, summarize() dropping the last group, relocate() honouring tidy-select helpers, NULL in mutate() behaving as dplyr does. Each of these is a small breaking change made to match the reference rather than to differ from it.
The pattern of tracking the polars floor upward every release and following tidyverse changes closely — .by in fill() arrived when tidyr 1.3.2 shipped it — suggests the next releases continue mirroring new dplyr and tidyr arguments rather than adding a distinct capability.
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 tidypolars.
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
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.
An MMRM tabulation package that has published nothing since its 2024 CRAN releases.
See all constants alternatives → · See all tidypolars alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. constants and tidypolars 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. constants and tidypolars 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 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.
Top tidypolars alternatives in Analytics are ranked by recent ship velocity. Browse the "tidypolars alternatives" section above for the current picks, or visit /alternatives/tidypolars for the full list with editorial commentary on each.