flexdashboard
flexdashboard has slowed to a fix-only trickle since the bslib theming rework
Comparison · Analytics
insight vs themis
A side-by-side editorial comparison of insight and themis — release velocity, themes, recent moves, and the top alternatives to consider.
insight vs themis: at a glance
What is insight?
insight quietly widens the set of model objects the easystats ecosystem can read
insight is the extraction layer under the easystats packages — it answers what a fitted model's parameters, data, variance and priors are, for whatever object it is handed. The 1.4.x and 1.5.x releases read as a steady widening of that support list: tidymodels workflows, cmdstanr fits, rstpm2 survival models, lavaan variance-covariance, mice imputations.
What is themis?
themis is back to adding real resampling algorithms after a documentation-heavy stretch.
themis supplies recipes steps for handling class imbalance in tidymodels. The 1.0.x line was consumed by documentation accuracy, message translation and internal consistency work. Version 1.1.0 returns to substance with two new under-sampling methods.
insight vs themis: editorial side-by-side
insight
0.0ANALYTICS
insight quietly widens the set of model objects the easystats ecosystem can read
◆ Current state
insight is the extraction layer under the easystats packages — it answers what a fitted model's parameters, data, variance and priors are, for whatever object it is handed. The 1.4.x and 1.5.x releases read as a steady widening of that support list: tidymodels workflows, cmdstanr fits, rstpm2 survival models, lavaan variance-covariance, mice imputations.
◆ Where it's heading
Two things move together here. The support list grows toward objects produced outside the easystats world, and performance work targets the helpers that everything else calls — compact_list(), is_empty_object(), find_parameters() on mgcv models. New functions appear occasionally (get_simulated(), vcovFPC()) but the center of gravity is coverage, not capability.
◆ Prediction
Expect further model classes to be added as downstream easystats packages need them, and continued alignment with R-devel behavior changes like the weighted-residuals revision.
themis
2.5ANALYTICS
themis is back to adding real resampling algorithms after a documentation-heavy stretch.
◆ Current state
themis supplies recipes steps for handling class imbalance in tidymodels. The 1.0.x line was consumed by documentation accuracy, message translation and internal consistency work. Version 1.1.0 returns to substance with two new under-sampling methods.
◆ Where it's heading
The package grows by adding algorithms rather than restructuring itself. tomek() was rewritten to handle multiple classes and drop the unbalanced dependency, case weights arrived at 1.0.0, and cluster-centroid and condensed-nearest-neighbour under-sampling arrive now — each shipped as both a recipes step and a direct-implementation function.
◆ Prediction
Expect further under- and over-sampling methods in the same paired form, as the package fills out coverage of the standard class-imbalance literature.
Alternatives to insight and themis
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 insight or themis.
finetune
finetune tracks tune's evolving contracts more than it advances racing itself
embed
embed keeps adding encoding steps while shedding its deep-learning dependencies
dtplyr
dtplyr stopped hijacking data.table objects and became an opt-in translator
dials
dials is quietly registering the tuning parameters for tidymodels' deep-learning push
dbplyr
dbplyr ends its two-year backend migration by dropping 1st edition support outright
See all insight alternatives → · See all themis alternatives →
Recent activity from insight and themis
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 10d agothemisthemis 1.1.0 adds cluster-centroid and CNN under-sampling
- 1mo agoinsightcompact_list() performance and lavaan variance-covariance support
- 2mo agoinsightcmdstanr support and finite-population-corrected variance
- 4mo agoinsightget_simulated() added; rstpm2 survival models supported
- 6mo agoinsightWeighted residuals revised to match R 4.6.0
- 6mo agoinsighttidymodels workflow objects become readable
- 8mo agoinsightlme4 convergence and fixest data extraction fixes
- 1y agothemisthemis 1.0.3 corrects resampling direction in documentation
- 2y agothemisthemis 1.0.2 makes internal consistency and speed changes
- 3y agothemisthemis 1.0.1 fixes upsampling errors when none is needed
- 4y agothemisthemis 1.0.0 adds case weights to up- and down-sampling
- 4y agothemisthemis 0.2.2 rewrites tomek() for multiclass, drops a dependency
Frequently asked questions
What is the difference between insight and themis?
They serve adjacent needs but don't currently overlap on shipped themes. themis 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 insight better than themis?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. themis 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 insight?
Top insight alternatives in Analytics are ranked by recent ship velocity. Browse the "insight alternatives" section above for the current picks, or visit /alternatives/insight for the full list with editorial commentary on each.
What are the best alternatives to themis?
Top themis alternatives in Analytics are ranked by recent ship velocity. Browse the "themis alternatives" section above for the current picks, or visit /alternatives/themis for the full list with editorial commentary on each.