silx
silx settles into maintenance a release after its PySide6 migration
A side-by-side editorial comparison of ggstatsplot and Holistics — release velocity, themes, recent moves, and the top alternatives to consider.
ggstatsplot reached 1.0 by adding tests, having outsourced its statistics years ago.
ggstatsplot produces ggplot2 graphics with statistical test results embedded in the subtitle and caption — comparisons, correlations, contingency tables, histograms. Since the 2019 refactoring that moved all statistical computation into the separate statsExpressions package, its own release notes have been dominated by upstream tracking: adapting to ggplot2, dplyr, purrr and easystats changes. The 1.0.0 release in April 2026 breaks that run with real additions to the contingency-table functions.
Holistics is adding governance to the AI layer it spent the summer building.
Holistics ships small, frequent notes - often one or two sentences - covering three strands at once: AI features in Explore and Chat, as-code control over presentation through AML, and workspace hygiene like file history and dark mode. The August entries turn to the AI layer's edges rather than its capabilities, with an AI user attribute for restricting what the assistant can reach. Several entries are barely a line long, so scope frequently has to be read from the headline.
ggstatsplot produces ggplot2 graphics with statistical test results embedded in the subtitle and caption — comparisons, correlations, contingency tables, histograms. Since the 2019 refactoring that moved all statistical computation into the separate statsExpressions package, its own release notes have been dominated by upstream tracking: adapting to ggplot2, dplyr, purrr and easystats changes. The 1.0.0 release in April 2026 breaks that run with real additions to the contingency-table functions.
The architecture explains the cadence. With statistics living in statsExpressions, ggstatsplot's own releases are mostly the tax of sitting on top of a fast-moving plotting and tidyverse stack — five of the six most recent entries change nothing a user would notice. When substantive work does arrive it clusters in the plotting layer's coverage of test families, as in 1.0.0's one-sample goodness-of-fit support and pairwise contingency analyses. The maintainer is also visibly deliberate about scope, having removed the normality-curve overlay in 0.12.4 for being unrelated to the analysis in question.
Expect continued parity work across the plot family — features that exist in one function being extended to its siblings, as goodness-of-fit support moved from ggpiestats to ggbarstats — punctuated by maintenance releases tracking ggplot2 and easystats.
Holistics ships small, frequent notes - often one or two sentences - covering three strands at once: AI features in Explore and Chat, as-code control over presentation through AML, and workspace hygiene like file history and dark mode. The August entries turn to the AI layer's edges rather than its capabilities, with an AI user attribute for restricting what the assistant can reach. Several entries are barely a line long, so scope frequently has to be read from the headline.
The AI work has moved through a recognizable sequence: capability first with chart suggestions, then observability with AI Chat Insights for admins, and now access control with an AI-specific user attribute. Alongside it, Holistics keeps pulling presentation into AML - custom charts, theme palettes, currency formats - so the things analysts used to click are versioned as code. File history is the join between the two threads, giving every dashboard, model, and dataset its own restorable timeline.
With capability, visibility, and access control now in place for the AI layer, the next step is likely audit or policy depth - logging what the assistant answered against which data - rather than new AI surfaces.
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 ggstatsplot or Holistics.
silx settles into maintenance a release after its PySide6 migration
Plotly is turning its cloud into a metered compute platform with an enterprise on-ramp.
aniread stops asking you to know which tracker wrote the file
Rho's release machinery finally produced a stable build — and it shipped no new product.
Usermaven closed the loop: data comes in from anywhere, and now it goes back out.
OpenCTI spends a release unblocking queues and hardening upserts
See all ggstatsplot alternatives → · See all Holistics alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. Holistics is currently shipping more aggressively (velocity 5.0 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Holistics is currently shipping more aggressively (velocity 5.0 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 Analytics products to evaluate alongside.
Top ggstatsplot alternatives in Analytics are ranked by recent ship velocity. Browse the "ggstatsplot alternatives" section above for the current picks, or visit /alternatives/ggstatsplot for the full list with editorial commentary on each.
Top Holistics alternatives in Analytics are ranked by recent ship velocity. Browse the "Holistics alternatives" section above for the current picks, or visit /alternatives/holistics for the full list with editorial commentary on each.