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Comparison · Analytics

ggstats vs hydroloom

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

Shared themes:r-package

ggstats vs hydroloom: at a glance

Featureggstatshydroloom
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesggplot2, data-visualization, likert, regression-modelshydrology, network-analysis, geospatial, r-package
Last editorial update1h ago4h ago
WebsiteVisit →Visit →

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.

Read the full ggstats trajectory →

What is hydroloom?

USGS puts a type system over its river network toolkit so errors surface at dispatch

hydroloom builds and navigates hydrologic flow networks, carrying functionality migrated out of nhdplusTools. Version 1.2.0 introduces an S3 class hierarchy — hy_topo, hy_leveled, hy_node, hy_flownetwork — assigned automatically by hy() and by producer functions, letting the package validate input at dispatch time and emit guided errors. Outlet detection is now defined explicitly: a row is an outlet when its toid is not in id, with reserved values, NA and implicit absence all accepted.

Read the full hydroloom trajectory →

ggstats vs hydroloom: editorial side-by-side

G
ggstats
ANALYTICS
0.0

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.

H
hydroloom
ANALYTICS
0.0

USGS puts a type system over its river network toolkit so errors surface at dispatch

◆ Current state

hydroloom builds and navigates hydrologic flow networks, carrying functionality migrated out of nhdplusTools. Version 1.2.0 introduces an S3 class hierarchy — hy_topo, hy_leveled, hy_node, hy_flownetwork — assigned automatically by hy() and by producer functions, letting the package validate input at dispatch time and emit guided errors. Outlet detection is now defined explicitly: a row is an outlet when its toid is not in id, with reserved values, NA and implicit absence all accepted.

◆ Where it's heading

The package spent its first releases porting and broadening — non-dendritic network support, divergence routing, subsetting that follows diversions out of a basin — and has now turned to making that surface safe to use. The class hierarchy is the structural expression of that turn: instead of every function re-checking whether a data frame has the columns it needs, the type carries the guarantee. The explicit outlet rule resolves a category of failure where valid networks errored on NA or orphan toid values.

◆ Prediction

The release notes flag that subclass attributes are stripped by standard dplyr operations, which is the kind of rough edge that usually generates follow-up work — expect attribute preservation or restoration helpers next.

Alternatives to ggstats and hydroloom

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 hydroloom.

See all ggstats alternatives → · See all hydroloom alternatives →

Recent activity from ggstats and hydroloom

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

  1. 2mo agohydroloomhydroloom v1.2.0
  2. 5mo agoggstatsgglikert_side() and total columns for Likert plots
  3. 5mo agohydroloomTest tolerances relaxed for CRAN Fedora checks
  4. 5mo agohydroloomNetwork subsetting and divergence-routed accumulation
  5. 7mo agoggstatsLikert functions accept survey objects
  6. 10mo agohydroloomSort and indexing fixes
  7. 11mo agoggstatsTable output for ggcoef_compare(); x-axis limits harmonised
  8. 1y agoggstatsggstats 0.10.0
  9. 1y agoggstatsCoefficient plots unified around ggcoef_model() with grouping
  10. 1y agoggstatsDiverging and Likert geoms redesigned; connector geoms added
  11. 1y agohydroloomUpmain and downmain navigation for non-dendritic networks
  12. 2y agohydroloomInitial release completing the nhdplusTools migration

Frequently asked questions

What is the difference between ggstats and hydroloom?

Both compete on the same themes — r-package — within Analytics. ggstats and hydroloom 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 ggstats better than hydroloom?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggstats and hydroloom 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 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 hydroloom?

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