rjdqa
rjdqa keeps refining one screen: the seasonal adjustment quality dashboard
A side-by-side editorial comparison of ggcorrplot and tidytransit — release velocity, themes, recent moves, and the top alternatives to consider.
ggcorrplot came back after four years and found its significance markers had been lying
ggcorrplot draws correlation matrices in ggplot2 with optional significance marking and hierarchical reordering. It sat untouched from late 2022 until mid-2026, then shipped 0.2.0 and 0.3.0 sixteen days apart. Between them they added the display options users had been requesting since 2016 and repaired a set of bugs where hc.order = TRUE silently changed which cells were marked significant.
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.
ggcorrplot draws correlation matrices in ggplot2 with optional significance marking and hierarchical reordering. It sat untouched from late 2022 until mid-2026, then shipped 0.2.0 and 0.3.0 sixteen days apart. Between them they added the display options users had been requesting since 2016 and repaired a set of bugs where hc.order = TRUE silently changed which cells were marked significant.
Both releases chase the same target: parity with the older corrplot package inside a ggplot2 object. Significance stars appended to coefficient labels, circle scaling, decimal control, then boxed cells and glyphs sized by absolute correlation — these are corrplot's visual vocabulary reimplemented where they can be composed with other ggplot2 layers. The bug fixes point the other way, at foundations: p-values matched to cells by name rather than row position, clustering computed on the unrounded matrix, tl.col actually applied.
With the corrplot look largely reproduced and the correctness backlog cleared, the remaining gap is the mixed upper/lower display corrplot supports; that is the natural next argument if the current release pace holds.
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 ggcorrplot 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 ggcorrplot alternatives → · See all tidytransit alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r — within Analytics. ggcorrplot 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggcorrplot 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.
Top ggcorrplot alternatives in Analytics are ranked by recent ship velocity. Browse the "ggcorrplot alternatives" section above for the current picks, or visit /alternatives/ggcorrplot 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.