fillpattern
Pattern fills for ggplot2, hardened against the ways users write sizes
Comparison · Analytics
ggstats vs palettecore
A side-by-side editorial comparison of ggstats and palettecore — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:data-visualization
ggstats vs palettecore: at a glance
What is ggstats?
ggstats keeps widening what a coefficient or Likert plot can be
ggstats extends ggplot2 with statistical plotting: model coefficient plots, Likert and diverging bar charts, proportion geometries and the helpers that make them behave. Recent releases have added an experimental gglikert_side(), left and right total columns for gglikert(), and survey-object support across the Likert family. Development is steady and CRAN-paced, with releases every two to three months.
What is palettecore?
Accessible palettes generated from one seed, with every audit number computed on the hex you actually get
palettecore generates sequential, diverging and categorical colour palettes from a single seed using CIEDE2000 arc-length spacing in OKLCH, and audits each one for colour-vision-deficiency separation, greyscale survival, gamut and WCAG contrast. It exists as a numpy-only Python core and an R mirror validated hex-exact against shared parity fixtures, plus a CLI the project describes as its agent-friendly entry point. Four releases landed inside 24 hours in late July.
ggstats vs palettecore: editorial side-by-side
ggstats
0.0ANALYTICS
ggstats keeps widening what a coefficient or Likert plot can be
◆ Current state
ggstats extends ggplot2 with statistical plotting: model coefficient plots, Likert and diverging bar charts, proportion geometries and the helpers that make them behave. Recent releases have added an experimental gglikert_side(), left and right total columns for gglikert(), and survey-object support across the Likert family. Development is steady and CRAN-paced, with releases every two to three months.
◆ Where it's heading
Two long-running threads. The coefficient side has been consolidating — ggcoef_multinom() and ggcoef_multicomponents() soft-deprecated in favour of a unified ggcoef_model() with group_by, plus new ggcoef_dodged() and ggcoef_faceted() variants. The Likert side keeps expanding outward instead, absorbing survey objects, total columns and side-by-side layouts. Underneath both is a steady tax of ggplot2 and vctrs compatibility work, including tracking the geom_errorbarh() deprecation in ggplot2 4.0.0.
◆ Prediction
Expect gglikert_side() to lose its experimental status once its interface settles, and the deprecated multinomial entry points to be removed in a future release now that ggcoef_model() covers their cases.
palettecore
6.3ANALYTICS
Accessible palettes generated from one seed, with every audit number computed on the hex you actually get
◆ Current state
palettecore generates sequential, diverging and categorical colour palettes from a single seed using CIEDE2000 arc-length spacing in OKLCH, and audits each one for colour-vision-deficiency separation, greyscale survival, gamut and WCAG contrast. It exists as a numpy-only Python core and an R mirror validated hex-exact against shared parity fixtures, plus a CLI the project describes as its agent-friendly entry point. Four releases landed inside 24 hours in late July.
◆ Where it's heading
The arc is about making the audit honest rather than making the palettes prettier. The 0.2.2 release, prompted by an external review, moved every diagnostic to compute on the 8-bit quantised hex codes actually returned rather than on internal floats — a change that flips results near thresholds and had been quietly overstating one deuteranopia score. The 0.4.0 helix kind and the vividness control extend the generator, but the same release also tightens its own claims, reframing helix as checked rather than assumed CVD-safe.
◆ Prediction
Given the pattern of auditing its own assertions, expect the next release to extend the cvd_luminance_monotonic diagnostic beyond helix to the other palette kinds.
Alternatives to ggstats and palettecore
Other Analytics 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 ggstats or palettecore.
gcube
gcube's recent releases are all packaging metadata, not simulation code
cubist
The R port of Quinlan's Cubist gets reproducibility fixes, not new modelling
ecodive
ecodive rebuilt itself into a broad diversity-metric library, breaking as it went
simStateSpace
State-space data simulation for R, filled in one function at a time
rollama
rollama turns a local-LLM wrapper into an instrument for reproducible annotation
See all ggstats alternatives → · See all palettecore alternatives →
Recent activity from ggstats and palettecore
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 24d agopalettecorepalettecore 0.4.0
- 24d agopalettecorepalettecore 0.2.2
- 24d agopalettecorepalettecore 0.2.1
- 24d agopalettecorepalettecore 0.2.0 ⚡
- 5mo agoggstatsgglikert_side() and total columns for Likert plots
- 7mo agoggstatsLikert functions accept survey objects
- 11mo agoggstatsTable output for ggcoef_compare(); x-axis limits harmonised
- 1y agoggstatsggstats 0.10.0
- 1y agoggstatsCoefficient plots unified around ggcoef_model() with grouping
- 1y agoggstatsDiverging and Likert geoms redesigned; connector geoms added
Frequently asked questions
What is the difference between ggstats and palettecore?
Both compete on the same themes — data-visualization — within Analytics. palettecore is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 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 ggstats better than palettecore?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. palettecore is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
What are the best alternatives to ggstats?
Top ggstats alternatives in Analytics are ranked by recent ship velocity. Browse the "ggstats alternatives" section above for the current picks, or visit /alternatives/ggstats for the full list with editorial commentary on each.
What are the best alternatives to palettecore?
Top palettecore alternatives in Analytics are ranked by recent ship velocity. Browse the "palettecore alternatives" section above for the current picks, or visit /alternatives/palettecore for the full list with editorial commentary on each.