← Back to home
Comparison · Analytics

ggstatsplot vs ichimoku

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

ggstatsplot vs ichimoku: at a glance

Featureggstatsplotichimoku
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesstatistical-plots, ggplot2, contingency-tables, hypothesis-testingfinancial-charting, technical-analysis, dependency-reduction, oanda
Last editorial update1h ago2h ago
WebsiteVisit →Visit →

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 →

What is ichimoku?

A cloud-chart package quietly swapping its dependencies for its maintainer's own libraries.

ichimoku implements Ichimoku Kinko Hyo cloud charts, strategy backtesting and an OANDA data interface for R. Recent releases are almost entirely plumbing: 1.5.7 drops RcppSimdJson in favor of secretbase for JSON parsing, following earlier releases that moved hashing to secretbase and raised the nanonext and mirai floors. The charting and strategy surface has been stable since the 1.5.0 line.

Read the full ichimoku trajectory →

ggstatsplot vs ichimoku: editorial side-by-side

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.

I
ichimoku
ANALYTICS
0.0

A cloud-chart package quietly swapping its dependencies for its maintainer's own libraries.

◆ Current state

ichimoku implements Ichimoku Kinko Hyo cloud charts, strategy backtesting and an OANDA data interface for R. Recent releases are almost entirely plumbing: 1.5.7 drops RcppSimdJson in favor of secretbase for JSON parsing, following earlier releases that moved hashing to secretbase and raised the nanonext and mirai floors. The charting and strategy surface has been stable since the 1.5.0 line.

◆ Where it's heading

The visible arc is consolidation onto the maintainer's own package family — secretbase for hashing and now JSON, nanonext and mirai for concurrency — which steadily removes third-party and Rcpp-based dependencies from the install chain. Feature work is sporadic and narrow when it comes: a faster POSIXct formatter exported as a utility, a multi-session option for the Shiny app, and a fix for asymmetric strategies that failed to emit a final entry signal.

◆ Prediction

Expect further dependency consolidation as the sibling packages gain capabilities, with ichimoku adopting them shortly after release rather than shipping new charting features.

Alternatives to ggstatsplot and ichimoku

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 ichimoku.

See all ggstatsplot alternatives → · See all ichimoku alternatives →

Recent activity from ggstatsplot and ichimoku

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

  1. 2mo agoichimokuJSON parsing moves from RcppSimdJson to secretbase
  2. 3mo agoggstatsplotPairwise contingency tests and one-sample goodness-of-fit
  3. 4mo agoggstatsplotInternal maintenance only
  4. 6mo agoggstatsplotAdapted to dplyr 1.2.0 and purrr 1.2.1
  5. 8mo agoggstatsplotContributor list updated in DESCRIPTION
  6. 10mo agoggstatsplotSecondary axis label parsing fixed in gghistostats
  7. 11mo agoggstatsplotAdapted to the latest ggplot2 release
  8. 1y agoichimokuFaster POSIXct formatting exported as a utility
  9. 1y agoichimokuMultiple concurrent sessions in the OANDA Shiny app
  10. 1y agoichimokuAsymmetric strategies now emit their final entry signal
  11. 2y agoichimokusecretbase floor raised to 1.0.0
  12. 2y agoichimokuArchive verification reverts to SHA256

Frequently asked questions

What is the difference between ggstatsplot and ichimoku?

They serve adjacent needs but don't currently overlap on shipped themes. ggstatsplot and ichimoku 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 ggstatsplot better than ichimoku?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggstatsplot and ichimoku 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 Analytics products to evaluate alongside.

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.

What are the best alternatives to ichimoku?

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