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ggeffects vs textrecipes

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

ggeffects vs textrecipes: at a glance

Featureggeffectstextrecipes
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesmarginal-effects, r-stats, statistics, breaking-changestext-processing, tidymodels, recipes, sparse-data
Last editorial update2h ago1h ago
WebsiteVisit →Visit →

What is ggeffects?

ggeffects hands its contrast engine to modelbased and keeps the interface

ggeffects computes and plots marginal effects for a long tail of R model classes. Its recent line has two threads: steadily broadening model support and argument surface, and repeatedly absorbing breaking changes from the packages it computes on top of. In 2.2.0 it stopped absorbing them and delegated test_predictions() and johnson_neyman() to modelbased instead.

Read the full ggeffects trajectory →

What is textrecipes?

Text features finally stay sparse all the way to the model.

textrecipes supplies the recipes steps for turning text into model-ready columns: tokenizing, hashing, term frequency, TF-IDF, and word embeddings. Version 1.1.0 added a sparse argument to step_dummy_hash(), step_texthash(), step_tf() and step_tfidf() so they emit sparse vectors. The releases before it are a long consistency pass — keep_original_cols on every step that creates columns, informative errors on name collisions, tunable arguments documented, integer rather than double output where integers are what is meant.

Read the full textrecipes trajectory →

ggeffects vs textrecipes: editorial side-by-side

G
ggeffects
ANALYTICS
0.0

ggeffects hands its contrast engine to modelbased and keeps the interface

◆ Current state

ggeffects computes and plots marginal effects for a long tail of R model classes. Its recent line has two threads: steadily broadening model support and argument surface, and repeatedly absorbing breaking changes from the packages it computes on top of. In 2.2.0 it stopped absorbing them and delegated test_predictions() and johnson_neyman() to modelbased instead.

◆ Where it's heading

The package is settling into a front-end role — a consistent predict_response() interface over other people's estimation engines — rather than owning the computation itself. The 2.x releases also show a pattern of removing deprecated arguments and clarifying mixed-model semantics, so the interface is being tightened as the backend is outsourced.

◆ Prediction

Expect the features lost in the modelbased handover to return as that package's contrast and slope estimation matures, rather than being reimplemented locally.

T
textrecipes
ANALYTICS
0.0

Text features finally stay sparse all the way to the model.

◆ Current state

textrecipes supplies the recipes steps for turning text into model-ready columns: tokenizing, hashing, term frequency, TF-IDF, and word embeddings. Version 1.1.0 added a sparse argument to step_dummy_hash(), step_texthash(), step_tf() and step_tfidf() so they emit sparse vectors. The releases before it are a long consistency pass — keep_original_cols on every step that creates columns, informative errors on name collisions, tunable arguments documented, integer rather than double output where integers are what is meant.

◆ Where it's heading

Two forces drive this package. One is memory: text produces wide, mostly-zero matrices, and the sparse work is the direct answer, landing in the same period that workflows learned to fit and predict on dgCMatrix input. The other is upstream churn — the tweets tokenizer was deprecated because tokenizers deprecated it, the politeness feature disappeared when textfeatures left Suggests. The package's own agenda is consistency; its release timing belongs to its dependencies.

◆ Prediction

Expect the sparse argument to spread to the remaining column-producing steps, since only four of them have it, and expect more steps to be reworked as recipes' own sparse-data support matures.

Alternatives to ggeffects and textrecipes

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 ggeffects or textrecipes.

See all ggeffects alternatives → · See all textrecipes alternatives →

Recent activity from ggeffects and textrecipes

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

  1. 1y agotextrecipesHashing and TF-IDF steps can emit sparse vectors
  2. 1y agoggeffectsggeffects delegates contrasts and slopes to modelbased
  3. 1y agotextrecipesstep_textfeatures() sped up; clean_levels NA bug fixed
  4. 1y agoggeffectsFive focal terms and formula-based contrast tests
  5. 1y agoggeffectsMixed-model predictions split type from interval
  6. 1y agoggeffectsBias correction for back-transformed mixed-model predictions
  7. 1y agoggeffectsSupport for WeightIt model classes
  8. 2y agoggeffectsglmgee support and vcov controls for ggemmeans()
  9. 2y agotextrecipestextfeatures dependency dropped; politeness feature removed
  10. 2y agotextrecipesuntokenize and normalization return factors
  11. 2y agotextrecipeskeep_original_cols everywhere; hashing column order fixed
  12. 3y agotextrecipesTunable arguments documented; name collisions now error

Frequently asked questions

What is the difference between ggeffects and textrecipes?

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

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

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

What are the best alternatives to textrecipes?

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