qqman
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
A side-by-side editorial comparison of symengine and tidypolars — release velocity, themes, recent moves, and the top alternatives to consider.
An R symbolic-maths binding whose changelog is really the C++ core's release notes.
symengine gives R access to the SymEngine computer algebra core for symbolic expressions, matrices and sets. The tracked feed carries the upstream C++ library's releases rather than R-binding changes, so what shows here is core work: parser fixes, locale-independent double parsing, an SOVERSION bump and matrix transpose corrections. Feature growth in the core has slowed considerably since the 0.9 and 0.10 releases.
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.
symengine gives R access to the SymEngine computer algebra core for symbolic expressions, matrices and sets. The tracked feed carries the upstream C++ library's releases rather than R-binding changes, so what shows here is core work: parser fixes, locale-independent double parsing, an SOVERSION bump and matrix transpose corrections. Feature growth in the core has slowed considerably since the 0.9 and 0.10 releases.
The upstream core has moved from adding capability — serialization, a first simplify(), set types, matrix expressions, LLVM support — toward maintenance: build fixes, dependency support such as Flint3, and correctness patches. For R users the practical consequence is that new symbolic features arrive only as fast as the binding exposes them, which this feed does not report on.
Expect further upstream maintenance releases tracking LLVM and Flint versions; nothing in these notes signals a new capability push.
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 symengine or tidypolars.
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 symengine 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. symengine 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. symengine 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 symengine alternatives in Analytics are ranked by recent ship velocity. Browse the "symengine alternatives" section above for the current picks, or visit /alternatives/symengine-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.