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Comparison · Analytics

hydroloom vs labelled

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

Shared themes:r-package

hydroloom vs labelled: at a glance

Featurehydroloomlabelled
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themeshydrology, network-analysis, geospatial, r-packagesurvey-data, data-labels, stata-spss, metadata
Last editorial update5h ago42m ago
WebsiteVisit →Visit →

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 →

What is labelled?

The bridge between Stata/SPSS labelled data and tidy R keeps widening, one integration at a time.

labelled manages variable labels, value labels and user-defined missing values on data imported from Stata, SPSS and SAS, filling the gap between those formats' metadata and R's native types. Recent releases have pushed outward from the core label accessors: survey design objects from the survey package are now supported throughout, look_for() results can be rendered as formatted gt tables, and dictionary data frames convert in both directions. Error messaging moved wholesale to cli in 2.14.0.

Read the full labelled trajectory →

hydroloom vs labelled: editorial side-by-side

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.

L
labelled
ANALYTICS
0.0

The bridge between Stata/SPSS labelled data and tidy R keeps widening, one integration at a time.

◆ Current state

labelled manages variable labels, value labels and user-defined missing values on data imported from Stata, SPSS and SAS, filling the gap between those formats' metadata and R's native types. Recent releases have pushed outward from the core label accessors: survey design objects from the survey package are now supported throughout, look_for() results can be rendered as formatted gt tables, and dictionary data frames convert in both directions. Error messaging moved wholesale to cli in 2.14.0.

◆ Where it's heading

The arc is toward being usable wherever labelled data ends up, not just where it is loaded. Each recent release either extends support to another object type — survey designs, packed columns, plain vectors, tibbles with list columns — or adds a conversion path between labels and some other representation. The look_for() search function has become a second centre of gravity alongside the label accessors, accumulating its own output formats and long-format conversions.

◆ Prediction

The pattern of adding compatibility with one more object type or output format per release is stable and likely continues. Nothing in these entries indicates a change to the underlying haven_labelled representation the package is built on.

Alternatives to hydroloom and labelled

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 hydroloom or labelled.

See all hydroloom alternatives → · See all labelled alternatives →

Recent activity from hydroloom and labelled

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

  1. 2mo agohydroloomhydroloom v1.2.0
  2. 5mo agohydroloomTest tolerances relaxed for CRAN Fedora checks
  3. 5mo agohydroloomNetwork subsetting and divergence-routed accumulation
  4. 9mo agolabelledFormatted look_for() tables and two-way dictionary conversion
  5. 10mo agohydroloomSort and indexing fixes
  6. 11mo agolabelledSurvey design objects supported across the package
  7. 1y agolabelledRegression in set_variable_labels() corrected
  8. 1y agolabelledcli adopted for all messaging; null_action gains options
  9. 1y agohydroloomUpmain and downmain navigation for non-dendritic networks
  10. 2y agolabelledCustom functions can rewrite variable and value labels in bulk
  11. 2y agohydroloomInitial release completing the nhdplusTools migration
  12. 3y agolabelledPacked columns supported and label attributes exposed directly

Frequently asked questions

What is the difference between hydroloom and labelled?

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

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

What are the best alternatives to labelled?

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