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Comparison · Infra & APIs

ggpointless vs usmapdata

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

Shared themes:r-packages

ggpointless vs usmapdata: at a glance

Featureggpointlessusmapdata
SectorInfra & APIsInfra & APIs
Velocity score0.02.5
Sparks · 30d00
Top themesggplot2-extensions, data-visualization, pictogram-charts, alpha-gradientsr-packages, geospatial, census-data, cartography
Last editorial update45m 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 usmapdata?

usmapdata ships its 2025 shapefiles on the year-indexed model it adopted in 0.4.0.

usmapdata supplies the boundary data behind usmap's plotting functions. Since 0.4.0 it has been year-indexed: us_map(data_year = ) selects a vintage, and each Census release is added as its own year with older ones still reachable. 1.1.0 adds 2025. 1.0.0 closed the package's longest-standing gap by adding Puerto Rico, retroactively across every vintage.

Read the full usmapdata trajectory →

ggpointless vs usmapdata: 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.

U
usmapdata
INFRA · APIS
2.5

usmapdata ships its 2025 shapefiles on the year-indexed model it adopted in 0.4.0.

◆ Current state

usmapdata supplies the boundary data behind usmap's plotting functions. Since 0.4.0 it has been year-indexed: us_map(data_year = ) selects a vintage, and each Census release is added as its own year with older ones still reachable. 1.1.0 adds 2025. 1.0.0 closed the package's longest-standing gap by adding Puerto Rico, retroactively across every vintage.

◆ Where it's heading

The package has settled into a predictable rhythm — one shapefile vintage per year, with structural change rare and clustered. The two changes that mattered were data_year in 0.4.0, which turned a single-vintage dataset into a time series, and the tibble-to-data-frame switch in 0.6.0 that reduced what downstream callers have to depend on.

◆ Prediction

The stated policy — each year added going forward, previous years reachable through data_year — points to a 2026 vintage as the next release. Nothing in these notes suggests further change to the data model.

Alternatives to ggpointless and usmapdata

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 usmapdata.

See all ggpointless alternatives → · See all usmapdata alternatives →

Recent activity from ggpointless and usmapdata

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

  1. 23d agousmapdata2025 Census shapefiles added
  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. 0y agousmapdataPuerto Rico added across every map vintage
  5. 1y agousmapdataus_map() returns a data frame instead of a tibble
  6. 1y agousmapdata2024 Census shapefiles added
  7. 1y agousmapdatadata_year turns the package into a multi-vintage archive
  8. 2y agousmapdataMap data moves to 2023 shapefiles
  9. 2y agoggpointlessgeom_catenary() draws a hanging chain
  10. 3y agoggpointlessgeom_chaikin() adds corner-cutting path smoothing
  11. 4y agoggpointlessgeom_lexis() and the female_leaders dataset

Frequently asked questions

What is the difference between ggpointless and usmapdata?

Both compete on the same themes — r-packages — within Infra & APIs. usmapdata is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is ggpointless better than usmapdata?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. usmapdata is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. 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 usmapdata?

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