STACAS
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
A side-by-side editorial comparison of tbrf and worldbank — release velocity, themes, recent moves, and the top alternatives to consider.
Time-based rolling statistics for water-quality data, finally getting plotting and padding built in.
tbrf computes rolling statistics over time windows rather than fixed row counts — geometric means, confidence intervals and related summaries indexed by date. That distinction matters for irregularly sampled environmental monitoring data, where a fixed-width window spans different amounts of real time. Version 0.1.7 folds in stat_stepribbon() from ggalt, ships an Entero example dataset for lognormal workflows, and adds na.pad across the tbr_ family.
A World Bank data wrapper that keeps finding the places its own API can't reach.
worldbank provides R access to the World Bank's public data: World Development Indicators, the Poverty and Inequality Platform, project records, and the Finances One datasets. It settled its type contract early — always a data.frame, never a conditional tibble — and has since layered on opt-in request caching, multi-indicator queries, and query conveniences like most-recent-values and gap filling. The most recent addition sidesteps the API entirely, pulling the full WDI archive as a zip.
tbrf computes rolling statistics over time windows rather than fixed row counts — geometric means, confidence intervals and related summaries indexed by date. That distinction matters for irregularly sampled environmental monitoring data, where a fixed-width window spans different amounts of real time. Version 0.1.7 folds in stat_stepribbon() from ggalt, ships an Entero example dataset for lognormal workflows, and adds na.pad across the tbr_ family.
The package spent its middle releases absorbing upstream breakage — a lubridate duration redefinition, a tibble 3.0.0 subassignment change, tidyselect internals. The 0.1.7 release breaks that pattern: it is the first in five years to add capability rather than repair it, and it does so by internalising a stat from an abandoned dependency instead of relying on it. Cadence remains very low, with a five-year gap between 0.1.5 and 0.1.6.
Absorbing stat_stepribbon() directly suggests further vendoring of the plotting layer rather than new statistical functions. The entries do not indicate which rolling statistics, if any, are queued next.
worldbank provides R access to the World Bank's public data: World Development Indicators, the Poverty and Inequality Platform, project records, and the Finances One datasets. It settled its type contract early — always a data.frame, never a conditional tibble — and has since layered on opt-in request caching, multi-indicator queries, and query conveniences like most-recent-values and gap filling. The most recent addition sidesteps the API entirely, pulling the full WDI archive as a zip.
Two threads run through the log. The first is query ergonomics: multiple indicators per call, mrv and gapfill parameters, regex search across the indicator catalog, a shorter wb_data() name that has since become the primary entry point. The second is coverage of things the standard API handles poorly — bulk download reaches footnote and series-time metadata the endpoints never expose, and PIP nowcasts and project records extend past the indicator tables most users start with. The maintainer runs the same infrastructure across their other data packages, and the caching design here is identical to what bbk and treasury received.
Expect the remaining rough edges of the World Bank's own API — inconsistent empty responses, metadata only available in bulk files — to keep driving releases, rather than a push into new data providers.
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 tbrf or worldbank.
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
A debugger for ggplot2's internals, hardening its grip as the internals it traces keep moving.
A univariate density estimator that added zero-inflated data and reopened its C++ API to do it.
Stationary vine copulas for time series, released in lockstep with the rest of Nagler's vine stack.
A single-purpose ggplot2 extension that has spent six years tracking ggplot2 instead of growing.
A Star Trek data package that became a Memory Alpha web client and has been patching scrapers ever since.
See all tbrf alternatives → · See all worldbank alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. tbrf and worldbank 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. tbrf and worldbank 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 tbrf alternatives in Analytics are ranked by recent ship velocity. Browse the "tbrf alternatives" section above for the current picks, or visit /alternatives/tbrf for the full list with editorial commentary on each.
Top worldbank alternatives in Analytics are ranked by recent ship velocity. Browse the "worldbank alternatives" section above for the current picks, or visit /alternatives/worldbank for the full list with editorial commentary on each.