rjdqa
rjdqa keeps refining one screen: the seasonal adjustment quality dashboard
A side-by-side editorial comparison of shapviz and tidytransit — release velocity, themes, recent moves, and the top alternatives to consider.
shapviz refines its SHAP plots release by release while chasing ggplot2's moving target.
shapviz turns SHAP values from XGBoost, LightGBM, H2O, kernelshap and other sources into standard diagnostic plots — importance, dependence, waterfall, force and interaction. Recent work is plot ergonomics: shared y-axis control across dependence plots, a bar view for interaction values, and axis collection via patchwork. The two most recent releases are pure compatibility and bug fixes.
tidytransit tracks the GTFS spec as it grows, one reader and one router feature at a time.
tidytransit reads GTFS transit feeds into tidy data frames and computes travel times using a RAPTOR implementation. Recent work splits between the reader keeping pace with the spec — locations.geojson in 1.7.0, empty strings parsed as NA in 1.8.0 — and the router gaining realism, most recently in-seat transfers. Feed specifications are now pulled from the automatically parsed GTFS reference rather than maintained by hand.
shapviz turns SHAP values from XGBoost, LightGBM, H2O, kernelshap and other sources into standard diagnostic plots — importance, dependence, waterfall, force and interaction. Recent work is plot ergonomics: shared y-axis control across dependence plots, a bar view for interaction values, and axis collection via patchwork. The two most recent releases are pure compatibility and bug fixes.
Two threads run in parallel here. One is visual refinement converging on conventions from Python's shap — the 0.10.0 notes openly float switching share_y to TRUE to match it. The other is connector maintenance, keeping pace with H2O, XGBoost 1.x and 2.x, shapr and permshap as each changes. Neither thread adds new explanation methods; shapviz's job is presentation, and it is being polished rather than extended.
Expect share_y = TRUE to become the default and further ggplot2 4.x fallout, with connector updates arriving as the upstream SHAP packages release.
tidytransit reads GTFS transit feeds into tidy data frames and computes travel times using a RAPTOR implementation. Recent work splits between the reader keeping pace with the spec — locations.geojson in 1.7.0, empty strings parsed as NA in 1.8.0 — and the router gaining realism, most recently in-seat transfers. Feed specifications are now pulled from the automatically parsed GTFS reference rather than maintained by hand.
The package has settled into tracking an external standard, which is why the changelog reads as a sequence of spec conformance items rather than a roadmap. Parsing responsibility keeps shifting outward to gtfsio, and data sources have moved with the ecosystem, from the retired transitfeeds API to MobilityData. Router changes are rarer than reader changes but land in the same releases.
Further GTFS spec features are the safest expectation, with GTFS-Flex the likeliest area now that locations.geojson reading is in place.
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 shapviz or tidytransit.
rjdqa keeps refining one screen: the seasonal adjustment quality dashboard
epikit narrows to field-epidemiology helpers, handing proportions to a sibling package
SimInf 10.0 turns an epidemic simulator into a tool that fits models to real time series
A young package porting Stata's egen row-wise helpers to the tidyverse, one function per release
A statistician's personal toolbox, growing one plotting utility at a time
R/qtl is in pure custodial mode: every recent release answers a compiler, not a user
See all shapviz alternatives → · See all tidytransit alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. shapviz and tidytransit 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. shapviz and tidytransit 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.
Top shapviz alternatives in Analytics are ranked by recent ship velocity. Browse the "shapviz alternatives" section above for the current picks, or visit /alternatives/shapviz for the full list with editorial commentary on each.
Top tidytransit alternatives in Analytics are ranked by recent ship velocity. Browse the "tidytransit alternatives" section above for the current picks, or visit /alternatives/tidytransit-r for the full list with editorial commentary on each.