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Comparison · Analytics

ggsci vs rjdqa

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

ggsci vs rjdqa: at a glance

Featureggscirjdqa
SectorAnalyticsAnalytics
Velocity score2.50.0
Sparks · 30d00
Top themescolor palettes, ggplot2, r, data visualizationofficial-statistics, seasonal-adjustment, quality-assurance, r-package
Last editorial update6h ago53m ago
WebsiteVisit →Visit →

What is ggsci?

ggsci quietly became a palette mirror, then taught itself to generate colors on demand

ggsci ships ready-made ggplot2 color scales, originally journal and sci-fi palettes and now overwhelmingly terminal themes — the iTerm collection has grown past 400 entries and picks up 30 to 70 more with each sync. The one structural change in the recent run is gephi_palettes(), which generates distinct categorical colors for an arbitrary number of levels rather than serving a fixed list. Release cadence is steady, roughly every six to eight weeks.

Read the full ggsci trajectory →

What is rjdqa?

rjdqa keeps refining one screen: the seasonal adjustment quality dashboard

rjdqa builds quality assessment dashboards for seasonal adjustment models produced by JDemetra+, aimed at official statisticians reviewing adjusted series. Essentially all development goes into two functions, simple_dashboard() and its denser variant simple_dashboard2(). Version 0.1.6 adds parameters to append observations to the forecast and to control whether the residual trading-days test is printed, defaulting to monthly series only, plus outlier table layout work and user-defined calendar regressor support in sc_dashboard().

Read the full rjdqa trajectory →

ggsci vs rjdqa: editorial side-by-side

G
ggsci
ANALYTICS
2.5

ggsci quietly became a palette mirror, then taught itself to generate colors on demand

◆ Current state

ggsci ships ready-made ggplot2 color scales, originally journal and sci-fi palettes and now overwhelmingly terminal themes — the iTerm collection has grown past 400 entries and picks up 30 to 70 more with each sync. The one structural change in the recent run is gephi_palettes(), which generates distinct categorical colors for an arbitrary number of levels rather than serving a fixed list. Release cadence is steady, roughly every six to eight weeks.

◆ Where it's heading

Two threads run in parallel. The larger one is curation: ggsci has effectively become a distribution channel for upstream color work, adding design-system palettes (Primer, Atlassian, Bootstrap, Tailwind) and re-syncing iTerm as that project changes, including correcting existing color values when upstream moves. The smaller and more interesting one is generation — the Gephi engine sidesteps the ceiling every fixed palette has, which is what happens when a plot needs more categories than any curated set provides.

◆ Prediction

Given how much of the release notes each cycle is a mechanical upstream sync, the plausible next step is automating those syncs rather than adding another vendor palette by hand; the Gephi generator is the more likely place any genuinely new capability appears.

R
rjdqa
ANALYTICS
0.0

rjdqa keeps refining one screen: the seasonal adjustment quality dashboard

◆ Current state

rjdqa builds quality assessment dashboards for seasonal adjustment models produced by JDemetra+, aimed at official statisticians reviewing adjusted series. Essentially all development goes into two functions, simple_dashboard() and its denser variant simple_dashboard2(). Version 0.1.6 adds parameters to append observations to the forecast and to control whether the residual trading-days test is printed, defaulting to monthly series only, plus outlier table layout work and user-defined calendar regressor support in sc_dashboard().

◆ Where it's heading

The package has converged on a single deliverable and is tuning it against reviewer practice. Each release adds a parameter that lets the analyst include or exclude one element of the dashboard, or adjusts how densely information is packed into the fixed space of the layout. The td_effect default — print the test only for monthly series — is characteristic: the knowledge about when a diagnostic is meaningful is being encoded into the tool rather than left to the reader.

◆ Prediction

The pattern of adding one toggle per diagnostic per release points at the same thing again, most likely another test given a conditional default, rather than a new dashboard function alongside the two that exist.

Alternatives to ggsci and rjdqa

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 ggsci or rjdqa.

See all ggsci alternatives → · See all rjdqa alternatives →

Recent activity from ggsci and rjdqa

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

  1. 15d agoggsciggsci 5.2.0
  2. 1mo agoggsciggsci 5.1.0
  3. 4mo agoggsciggsci 5.0.0 generates categorical colors instead of serving a fixed list
  4. 4mo agoggsciggsci 4.3.0
  5. 8mo agoggsciggsci 4.2.0
  6. 9mo agorjdqaForecast observations and conditional trading-days test in dashboards
  7. 9mo agoggsciggsci 4.1.0
  8. 1y agorjdqaFix tail() usage on ts objects
  9. 2y agorjdqaFix dependency minimums and outlier ordering
  10. 2y agorjdqasimple_dashboard2() added; deprecated sa_dashboard() removed
  11. 2y agorjdqasimple_dashboard() introduced; sa_dashboard() deprecated
  12. 7y agorjdqaFirst CRAN release

Frequently asked questions

What is the difference between ggsci and rjdqa?

They serve adjacent needs but don't currently overlap on shipped themes. ggsci is currently shipping more aggressively (velocity 2.5 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.

Is ggsci better than rjdqa?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggsci is currently shipping more aggressively (velocity 2.5 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.

What are the best alternatives to ggsci?

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

What are the best alternatives to rjdqa?

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