rjdqa
rjdqa keeps refining one screen: the seasonal adjustment quality dashboard
A side-by-side editorial comparison of oblicubes and tidypolars — release velocity, themes, recent moves, and the top alternatives to consider.
A tiny grid renderer for oblique-projection cubes, complete since its first release.
oblicubes draws 3D cubes and cuboids in oblique projection as grid grobs, with ggplot2 geom wrappers and a height-matrix helper for turning elevation data into coordinates. The entire feature set arrived in the initial 0.1.2 release, adapted from coolbutuseless's isocubes and cj-holmes's isocuboids. The two releases since have widened compatibility rather than added anything.
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.
oblicubes draws 3D cubes and cuboids in oblique projection as grid grobs, with ggplot2 geom wrappers and a height-matrix helper for turning elevation data into coordinates. The entire feature set arrived in the initial 0.1.2 release, adapted from coolbutuseless's isocubes and cj-holmes's isocuboids. The two releases since have widened compatibility rather than added anything.
The package is finished and its maintainer is treating it that way. 1.0.0 removed the R 4.1 native pipe from examples specifically so earlier R versions could use it — reaching backward, not forward — and added image alt text. The only change since is swapping a deprecated dplyr call in examples.
Expect nothing beyond occasional dependency deprecation fixes; the release pattern shows a small, deliberately complete package being kept installable.
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 oblicubes or tidypolars.
rjdqa keeps refining one screen: the seasonal adjustment quality dashboard
epikit narrows to field-epidemiology helpers, handing proportions to a sibling package
SimInf 10.0 turns an epidemic simulator into a tool that fits models to real time series
A young package porting Stata's egen row-wise helpers to the tidyverse, one function per release
A statistician's personal toolbox, growing one plotting utility at a time
R/qtl is in pure custodial mode: every recent release answers a compiler, not a user
See all oblicubes alternatives → · See all tidypolars alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r — within Analytics. oblicubes 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. oblicubes 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 oblicubes alternatives in Analytics are ranked by recent ship velocity. Browse the "oblicubes alternatives" section above for the current picks, or visit /alternatives/oblicubes-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.