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Comparison · Infra & APIs

ggpointless vs statpsych

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

ggpointless vs statpsych: at a glance

Featureggpointlessstatpsych
SectorInfra & APIsInfra & APIs
Velocity score0.00.0
Sparks · 30d00
Top themesggplot2-extensions, data-visualization, pictogram-charts, alpha-gradientspsychometrics, confidence-intervals, sample-size, statistical-power
Last editorial update1h ago4h 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 statpsych?

A statistics catalogue for psychology that grows by the release and rarely changes shape.

statpsych supplies confidence intervals, hypothesis tests, power calculations and sample-size planning for the designs psychology researchers actually run, exposed as several hundred small named functions rather than a modelling framework. Version 2.0.0 adds eight functions across logistic model performance, Kendall tau-a intervals and sample sizes, intraclass correlation testing, Geary kurtosis and Mann-Whitney power, and retires three names in favour of generalised replacements. The major version number reflects those removals rather than a change in how the package is used.

Read the full statpsych trajectory →

ggpointless vs statpsych: 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.

S
statpsych
INFRA · APIS
0.0

A statistics catalogue for psychology that grows by the release and rarely changes shape.

◆ Current state

statpsych supplies confidence intervals, hypothesis tests, power calculations and sample-size planning for the designs psychology researchers actually run, exposed as several hundred small named functions rather than a modelling framework. Version 2.0.0 adds eight functions across logistic model performance, Kendall tau-a intervals and sample sizes, intraclass correlation testing, Geary kurtosis and Mann-Whitney power, and retires three names in favour of generalised replacements. The major version number reflects those removals rather than a change in how the package is used.

◆ Where it's heading

Every release in this window is the same shape: a list of new functions, occasionally a rename. The package grows by filling cells in a grid of estimand, design and inferential goal, and 2.0.0 is notable only for finally deleting the three names its generalised replacements had superseded. That makes it a reference library whose value is coverage and stability, not direction, and the entries give no sign of that changing.

◆ Prediction

Expect the accretion to continue along the same axes, with sample-size and power counterparts filled in for estimands that currently have interval functions but no planning ones. The 2.0.0 deletions suggest occasional consolidation passes when a generalised function makes older specific ones redundant.

Alternatives to ggpointless and statpsych

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 statpsych.

See all ggpointless alternatives → · See all statpsych alternatives →

Recent activity from ggpointless and statpsych

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

  1. 1mo agostatpsychKendall tau, logistic fit measures added; three names retired
  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. 7mo agostatpsychIntraclass correlation and diversity indices gain full coverage
  5. 1y agostatpsychstatpsych 1.8
  6. 2y agostatpsychCorrelation tests and finite-population corrections added
  7. 2y agoggpointlessgeom_catenary() draws a hanging chain
  8. 2y agostatpsychCoefficient of variation and 2x2 within-subjects effects
  9. 3y agostatpsychPower calculations added for means, proportions and correlations
  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 statpsych?

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

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

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