rollupTree
The recursive-computation engine under massProps grows the accessors its consumer needed
A side-by-side editorial comparison of ggpointless and ipeaplot — release velocity, themes, recent moves, and the top alternatives to consider.
ggpointless keeps adding the ggplot2 layers nobody else bothered to write.
ggpointless is a small ggplot2 extension collecting geoms that sit outside the standard set — Lexis diagrams, Chaikin-smoothed paths, hanging chains, Fourier reconstructions — and it has grown steadily rather than changed shape. The May release is the largest yet: isotype and pictogram bar charts as stacks of discrete unit cells, a family of geoms that fade paths, segments, curves and reference lines along their length, and geom_gridline(), which draws grid lines as a layer on top of the data rather than beneath it.
An institutional chart theme whose recent releases are all vignette repair.
ipeaplot supplies Ipea's house style to ggplot2 — theme_ipea(), matching colour and fill scales, and export helpers that write the formats the institute's publications need. The feature line has been quiet since October, when save_ipeaplot() consolidated the format-specific savers. Both July releases exist to get the package building again, not to change it.
ggpointless is a small ggplot2 extension collecting geoms that sit outside the standard set — Lexis diagrams, Chaikin-smoothed paths, hanging chains, Fourier reconstructions — and it has grown steadily rather than changed shape. The May release is the largest yet: isotype and pictogram bar charts as stacks of discrete unit cells, a family of geoms that fade paths, segments, curves and reference lines along their length, and geom_gridline(), which draws grid lines as a layer on top of the data rather than beneath it.
Two patterns are visible. Ideas get generalized rather than left as one-offs: geom_area_fade() in the previous release established alpha gradients via grid::linearGradient(), and the recent release spreads that treatment across paths, lines, steps, segments, curves and the three reference-line geoms, each with the same fade_direction and alpha_fade_to arguments. And each new geom is expected to survive real plots — the unit charts work under coord_equal, coord_polar, coord_radial, coord_flip and faceting, and geom_gridline reads positions from trained scales and inherits styling from the theme's panel grid. The package also tracks ggplot2 closely, requiring 4.0.0 and using make_constructor() and gg_par() internally, and it dropped its bundled datasets outright rather than maintain stale copies.
The fade treatment now covers most path-like geoms but not the area and ribbon family beyond geom_area_fade(), which is where the pattern has room left to run. The unit-cell charts arrive with a label helper and no fill or grouping variants, so those are the plausible next additions.
ipeaplot supplies Ipea's house style to ggplot2 — theme_ipea(), matching colour and fill scales, and export helpers that write the formats the institute's publications need. The feature line has been quiet since October, when save_ipeaplot() consolidated the format-specific savers. Both July releases exist to get the package building again, not to change it.
The package has been converging on a smaller, more uniform surface: separate save_eps() and save_pdf() helpers gave way to one save_ipeaplot() covering vector and raster formats with sensible defaults, and the Frutiger font dependency was dropped for a default sans-serif. What consumes releases now is downstream breakage — two consecutive patches in ten days, the second traced to geobr, both in vignettes rather than package code.
The palette line has grown one colour set at a time and is the most likely place for the next addition, but nothing in these entries commits to it. On current evidence the near term is more compatibility patching against the geobr and ggplot2 packages the vignettes depend on.
Other Infra & APIs 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 ggpointless or ipeaplot.
The recursive-computation engine under massProps grows the accessors its consumer needed
A mass-properties rollup spends a year on documentation and follows its sibling's API
Six months of releases and not one of them touched the scoring models
A cognitive-science sampling package ships once, then goes quiet for eighteen months
A Bayesian volatility sampler in its maintenance decade, paying for its own speed
A black-box interpreter reaches CRAN, then learns multi-class and survival responses
See all ggpointless alternatives → · See all ipeaplot alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — data-visualization, r-packages — within Infra & APIs. ggpointless and ipeaplot 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. ggpointless and ipeaplot 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 Infra & APIs products to evaluate alongside.
Top ggpointless alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "ggpointless alternatives" section above for the current picks, or visit /alternatives/ggpointless for the full list with editorial commentary on each.
Top ipeaplot alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "ipeaplot alternatives" section above for the current picks, or visit /alternatives/ipeaplot for the full list with editorial commentary on each.