pins
pins keeps adding a storage backend per release while retiring its original API
Comparison · Analytics
insight vs scales
A side-by-side editorial comparison of insight and scales — release velocity, themes, recent moves, and the top alternatives to consider.
insight vs scales: 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 scales?
scales keeps widening what ggplot2 can put on an axis.
scales supplies the breaks, labels and transformations behind ggplot2's axes and legends. Unlike much of the tidyverse infrastructure around it, it still ships genuine feature work each release: native timespan handling in 1.3.0, then custom range-training classes and label_glue() in 1.4.0.
insight vs scales: 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.
scales
0.0ANALYTICS
scales keeps widening what ggplot2 can put on an axis.
◆ Current state
scales supplies the breaks, labels and transformations behind ggplot2's axes and legends. Unlike much of the tidyverse infrastructure around it, it still ships genuine feature work each release: native timespan handling in 1.3.0, then custom range-training classes and label_glue() in 1.4.0.
◆ Where it's heading
The arc runs toward extensibility and type coverage. First came built-in support for awkward types like difftime and hms; 1.4.0 inverts that by letting any third-party class participate in range training simply by implementing range() or levels(). Labelling is getting more expressive rather than merely more numerous.
◆ Prediction
Expect continued type-support and labelling work, with extension points that let downstream packages plug in their own classes instead of scales enumerating every one.
Alternatives to insight and scales
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 scales.
tsibble
tsibble shipped one release in five and a half years - the data structure is finished
yardstick
yardstick made fairness metrics a first-class part of tidymodels evaluation
tune
tune extends tuning past the model itself to postprocessors, and adds a second parallel backend
leaflet
leaflet relicensed to MIT and finished migrating off R's retired spatial stack
ggpubr
ggpubr reached 1.0.0 with p-value formatting presets for specific journals
See all insight alternatives → · See all scales alternatives →
Recent activity from insight and scales
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 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 agoscalesscales 1.4.0 opens range training to custom classes
- 2y agoscalesscales 1.3.0 makes timespans first-class on axes
- 3y agoscalesscales 1.2.1 re-documents to fix .Rd HTML issues
- 4y agoscalesscales 1.2.0 fixes currency sign order and adds scale_cut
- 6y agoscalesscales 1.1.1 fixes palette inversion and adds oob_keep()
- 6y agoscalesscales 1.1.0 reorganises breaks and labels into a naming scheme
Frequently asked questions
What is the difference between insight and scales?
They serve adjacent needs but don't currently overlap on shipped themes. insight and scales 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 insight better than scales?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. insight and scales 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 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 scales?
Top scales alternatives in Analytics are ranked by recent ship velocity. Browse the "scales alternatives" section above for the current picks, or visit /alternatives/scales-r for the full list with editorial commentary on each.