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Comparison · Infra & APIs

ggpointless vs PINstimation

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

ggpointless vs PINstimation: at a glance

FeatureggpointlessPINstimation
SectorInfra & APIsInfra & APIs
Velocity score0.00.0
Sparks · 30d00
Top themesggplot2-extensions, data-visualization, pictogram-charts, alpha-gradientsmarket-microstructure, finance, informed-trading, r-package
Last editorial update2h ago48m 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 PINstimation?

A market-microstructure toolkit that keeps adding estimators as the papers land.

PINstimation estimates probability-of-informed-trading models — PIN, multilayer PIN, adjusted PIN and VPIN — from trade and quote data, and handles the trade classification and aggregation that feeds them. The current 0.2.0 adds ivpin(), a maximum-likelihood variant of VPIN from Ke and Lin (2017). The package's early history is compressed into a single hour of backfilled tags in October 2022, so version order there does not track release order.

Read the full PINstimation trajectory →

ggpointless vs PINstimation: 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.

P
PINstimation
INFRA · APIS
0.0

A market-microstructure toolkit that keeps adding estimators as the papers land.

◆ Current state

PINstimation estimates probability-of-informed-trading models — PIN, multilayer PIN, adjusted PIN and VPIN — from trade and quote data, and handles the trade classification and aggregation that feeds them. The current 0.2.0 adds ivpin(), a maximum-likelihood variant of VPIN from Ke and Lin (2017). The package's early history is compressed into a single hour of backfilled tags in October 2022, so version order there does not track release order.

◆ Where it's heading

Each release tracks the literature: a Bayesian PIN estimator from Griffin et al., an improved VPIN from Ke and Lin, initial-parameter generation realigned to Ersan and Ghachem. The other steady thread is data handling — matrix inputs so the estimators compose with rolling windows, user-specified aggregation frequencies, and now quote leads as well as lags. The three-year gap between 0.1.2 and 0.2.0 makes this a slow, publication-paced package rather than an actively developed one.

◆ Prediction

On this pattern the next release adds whatever estimator the authors publish next, since two of the three feature releases here implement a specific paper. Nothing in the entries points to a change in the package's structure.

Alternatives to ggpointless and PINstimation

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 PINstimation.

See all ggpointless alternatives → · See all PINstimation alternatives →

Recent activity from ggpointless and PINstimation

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

  1. 3mo agoggpointlessPictogram unit charts, gridline layers and a family of fading geoms
  2. 5mo agoggpointlessFourier and arch geoms, area fades and glowing points
  3. 8mo agoPINstimationPINstimation 0.2.0
  4. 2y agoggpointlessgeom_catenary() draws a hanging chain
  5. 3y agoPINstimationPINstimation v0.1.2
  6. 3y agoPINstimationPINstimation v0.1.1
  7. 3y agoPINstimationPINstimation v0.0.1-beta
  8. 3y agoPINstimationPINstimation v0.1.0
  9. 3y agoggpointlessgeom_chaikin() adds corner-cutting path smoothing
  10. 4y agoggpointlessgeom_lexis() and the female_leaders dataset

Frequently asked questions

What is the difference between ggpointless and PINstimation?

They serve adjacent needs but don't currently overlap on shipped themes. ggpointless and PINstimation 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 PINstimation?

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

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