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Comparison · Infra & APIs

ggpointless vs remap

A side-by-side editorial comparison of ggpointless and remap — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-packages

ggpointless vs remap: at a glance

Featureggpointlessremap
SectorInfra & APIsInfra & APIs
Velocity score0.00.0
Sparks · 30d00
Top themesggplot2-extensions, data-visualization, pictogram-charts, alpha-gradientsspatial-modeling, geostatistics, r-packages, maintenance-mode
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

What is ggpointless?

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.

Read the full ggpointless trajectory →

What is remap?

A regional-model smoother in long-term maintenance, four years past its last real feature.

remap fits separate models to geographic regions and blends their predictions into a continuous surface, using the min_n nearest observations so region boundaries do not show as discontinuities. The methodological work is finished — the last behavioural change landed in 2022, and everything since has been unit handling, compiler warnings, dependency compatibility and citation updates. The July release is one such patch.

Read the full remap trajectory →

ggpointless vs remap: editorial side-by-side

G
ggpointless
INFRA · APIS
0.0

ggpointless keeps adding the ggplot2 layers nobody else bothered to write.

◆ Current state

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.

◆ Where it's heading

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.

◆ Prediction

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.

R
remap
INFRA · APIS
0.0

A regional-model smoother in long-term maintenance, four years past its last real feature.

◆ Current state

remap fits separate models to geographic regions and blends their predictions into a continuous surface, using the min_n nearest observations so region boundaries do not show as discontinuities. The methodological work is finished — the last behavioural change landed in 2022, and everything since has been unit handling, compiler warnings, dependency compatibility and citation updates. The July release is one such patch.

◆ Where it's heading

This is a stable academic package tracking its ecosystem rather than growing. The visible pattern is reactive maintenance: sf's 1.0.0 transition, ggplot2's size-to-linewidth rename, a gcc-UBSAN error on zero-point distance calculations, and now a check that distance matrices passed to remap() and predict() are converted to kilometres. Note that the feed's timestamps invert the version order — 0.3.1 is stamped seconds after 0.3.2 despite being the earlier release, so recency in this feed is not a reliable guide to sequence.

◆ Prediction

Nothing in these entries points to new capability. The realistic expectation is more of the same: a patch whenever sf, ggplot2 or a CRAN check surfaces an incompatibility, at roughly the observed cadence of one release every year or two.

Alternatives to ggpointless and remap

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 remap.

See all ggpointless alternatives → · See all remap alternatives →

Recent activity from ggpointless and remap

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 1mo agoremapDistance matrices now converted to kilometres automatically
  2. 3mo agoggpointlessPictogram unit charts, gridline layers and a family of fading geoms
  3. 5mo agoggpointlessFourier and arch geoms, area fades and glowing points
  4. 1y agoremapCitation updated to the R Journal article
  5. 1y agoremapUBSAN fix, parallel patch and sf search-path independence
  6. 2y agoggpointlessgeom_catenary() draws a hanging chain
  7. 3y agoremappredict() can return an upper bound on combined standard errors
  8. 3y agoggpointlessgeom_chaikin() adds corner-cutting path smoothing
  9. 4y agoggpointlessgeom_lexis() and the female_leaders dataset
  10. 5y agoremapRegions without observations no longer break the prediction surface

Frequently asked questions

What is the difference between ggpointless and remap?

Both compete on the same themes — r-packages — within Infra & APIs. ggpointless and remap 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.

Is ggpointless better than remap?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggpointless and remap 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.

What are the best alternatives to ggpointless?

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.

What are the best alternatives to remap?

Top remap alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "remap alternatives" section above for the current picks, or visit /alternatives/remap for the full list with editorial commentary on each.