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Comparison · Analytics

ApexCharts vs ggstatsplot

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

ApexCharts vs ggstatsplot: at a glance

FeatureApexChartsggstatsplot
SectorAnalyticsAnalytics
Velocity score10.00.0
Sparks · 30d30
Top themescharting, raw-data-input, chart-morphing, premium-tieringstatistical-plots, ggplot2, contingency-tables, hypothesis-testing
Last editorial update1d ago3d ago
WebsiteVisit →Visit →

What is ApexCharts?

Licensing settled, ApexCharts is back to changing what a chart can take as input.

ApexCharts is deep into a fast v6 line, shipping roughly weekly. The licensing arc that dominated 6.5 through 6.7 — trial watermarks, the first premium-gated chart type, then entitlement checks — has settled, and the last three releases are library work again. 6.9.0 is the largest of them: a histogram type that bins raw samples, a morph engine that conserves marks across chart types, and the end of the library's dependency-free packaging.

Read the full ApexCharts trajectory →

What is ggstatsplot?

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.

Read the full ggstatsplot trajectory →

ApexCharts vs ggstatsplot: editorial side-by-side

A
ApexCharts
ANALYTICS
10.0

Licensing settled, ApexCharts is back to changing what a chart can take as input.

◆ Current state

ApexCharts is deep into a fast v6 line, shipping roughly weekly. The licensing arc that dominated 6.5 through 6.7 — trial watermarks, the first premium-gated chart type, then entitlement checks — has settled, and the last three releases are library work again. 6.9.0 is the largest of them: a histogram type that bins raw samples, a morph engine that conserves marks across chart types, and the end of the library's dependency-free packaging.

◆ Where it's heading

The through-line now is input and arrangement rather than catalogue size. Charts increasingly accept the measurements a team actually has instead of pre-aggregated values, and the seams that let you hand a chart its own layout — plotOptions.unit.positions, the pluggable layout hook — are being filled in with kits rather than hard-coded options. The premium boundary has stopped moving; the free catalogue keeps growing around it.

◆ Prediction

Expect the raw-observation pattern to reach another chart type now that the bar pathway handles binning, and expect the remaining pluggable seams to get companion kits the way positions just did.

G
ggstatsplot
ANALYTICS
0.0

ggstatsplot reached 1.0 by adding tests, having outsourced its statistics years ago.

◆ Current state

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.

◆ Where it's heading

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.

◆ Prediction

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.

Alternatives to ApexCharts and ggstatsplot

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 ApexCharts or ggstatsplot.

See all ApexCharts alternatives → · See all ggstatsplot alternatives →

Recent activity from ApexCharts and ggstatsplot

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

  1. 1d agoApexChartsUnit charts get a 39-shape companion kit
  2. 2d agoApexChartsHistogram bins raw samples; charts morph between types
  3. 9d agoApexChartsPer-data-point label offsets land as functions
  4. 10d agoApexChartsPie and donut slice clicks work again after a 6.7.0 regression
  5. 16d agoApexChartsSunburst charts arrive; premium features now need an entitled plan
  6. 22d agoApexChartsUnit chart is the first premium-gated chart type
  7. 3mo agoggstatsplotPairwise contingency tests and one-sample goodness-of-fit
  8. 4mo agoggstatsplotInternal maintenance only
  9. 6mo agoggstatsplotAdapted to dplyr 1.2.0 and purrr 1.2.1
  10. 8mo agoggstatsplotContributor list updated in DESCRIPTION
  11. 10mo agoggstatsplotSecondary axis label parsing fixed in gghistostats
  12. 11mo agoggstatsplotAdapted to the latest ggplot2 release

Frequently asked questions

What is the difference between ApexCharts and ggstatsplot?

They serve adjacent needs but don't currently overlap on shipped themes. ApexCharts is currently shipping more aggressively (velocity 10.0 vs 0.0), with 3 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 ApexCharts better than ggstatsplot?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ApexCharts is currently shipping more aggressively (velocity 10.0 vs 0.0), with 3 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 ApexCharts?

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

What are the best alternatives to ggstatsplot?

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.