← Back to home
Comparison · Analytics

labelled vs TidyDensity

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

Shared themes:tidyverser-package

labelled vs TidyDensity: at a glance

FeaturelabelledTidyDensity
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themessurvey-data, data-labels, stata-spss, metadatastatistical-distributions, random-generation, parameter-estimation, tidyverse
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

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 →

What is TidyDensity?

A distribution catalogue that grows by one family at a time, and rarely breaks anything.

TidyDensity generates tidy-format random data from statistical distributions, with parameter estimation, AIC calculation, summary tables and automatic plotting for each one. Its releases follow a fixed template — breaking changes, new features, minor fixes — and the breaking section is usually empty. Growth comes distribution by distribution: Bernoulli, Burr, triangular, chi-square, zero-truncated negative binomial and others each arrive with a matching set of param_estimate, aic and stats_tbl helpers.

Read the full TidyDensity trajectory →

labelled vs TidyDensity: editorial side-by-side

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.

T
TidyDensity
ANALYTICS
0.0

A distribution catalogue that grows by one family at a time, and rarely breaks anything.

◆ Current state

TidyDensity generates tidy-format random data from statistical distributions, with parameter estimation, AIC calculation, summary tables and automatic plotting for each one. Its releases follow a fixed template — breaking changes, new features, minor fixes — and the breaking section is usually empty. Growth comes distribution by distribution: Bernoulli, Burr, triangular, chi-square, zero-truncated negative binomial and others each arrive with a matching set of param_estimate, aic and stats_tbl helpers.

◆ Where it's heading

The package is filling out a matrix rather than changing shape — every new distribution gets the same four or five companion functions, so the surface grows predictably and the design does not. What variation exists comes from utilities that work across distributions: MCMC sampling, bootstrap helpers, time series conversion, distribution comparison. The two genuine breaking changes in this window were both internal reworks, moving generation onto data.table and rewriting quantile normalization for speed.

◆ Prediction

The established pattern of adding a distribution with its full helper set is the most likely continuation. Recent releases have been small, suggesting the catalogue is approaching the distributions its author considers worth covering.

Alternatives to labelled and TidyDensity

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 labelled or TidyDensity.

See all labelled alternatives → · See all TidyDensity alternatives →

Recent activity from labelled and TidyDensity

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

  1. 9mo agolabelledFormatted look_for() tables and two-way dictionary conversion
  2. 11mo agolabelledSurvey design objects supported across the package
  3. 11mo agoTidyDensityquantile_normalize rewritten, changing its output
  4. 1y agoTidyDensityDocumentation corrections for two distribution functions
  5. 1y agolabelledRegression in set_variable_labels() corrected
  6. 1y agolabelledcli adopted for all messaging; null_action gains options
  7. 2y agoTidyDensityZero-truncated distributions and AIC helpers added in bulk
  8. 2y agoTidyDensityMCMC sampling and quantile normalization join the utilities
  9. 2y agolabelledCustom functions can rewrite variable and value labels in bulk
  10. 2y agoTidyDensityGeneration moves to data.table; native pipe raises the R floor
  11. 2y agoTidyDensityDistributions convertible to time series objects
  12. 3y agolabelledPacked columns supported and label attributes exposed directly

Frequently asked questions

What is the difference between labelled and TidyDensity?

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

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

What are the best alternatives to TidyDensity?

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