simlandr
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
A side-by-side editorial comparison of eiaapi and rfm — release velocity, themes, recent moves, and the top alternatives to consider.
A thin EIA energy-data client whose whole story is making bulk queries survive the API's limits.
eiaapi wraps the US Energy Information Administration API: eia_get() issues a single query, and eia_backfill() decomposes a large date range into chunks the API will actually serve. Three releases across two years cover the package's entire history, and the second and third both exist because of eia_backfill().
A customer segmentation package that went quiet for six years and returned with dependency hygiene
rfm computes recency, frequency and monetary segmentation for customer analytics in R. The feature surface was set early: 0.1.0 shipped a Shiny app and customer-level input, 0.2.0 added default segments and median statistics, 0.2.1 added user-specified score thresholds and returnable plot objects. Then nothing for nearly six years. Version 0.4.0 in April 2026 fixes a missing-column error and a customer id fault, and moves plotly and gganimate from Suggests to Imports.
eiaapi wraps the US Energy Information Administration API: eia_get() issues a single query, and eia_backfill() decomposes a large date range into chunks the API will actually serve. Three releases across two years cover the package's entire history, and the second and third both exist because of eia_backfill().
The package's development is a single problem being worked: pulling more data than one request allows. Version 0.1.2 introduced eia_backfill() for exactly that, and 0.2.0 fixed it for non-hourly frequencies by adding the frequency and data arguments so it matches eia_get()'s interface and by reworking Date handling. That convergence of the two functions' signatures is the visible design direction — one query idiom regardless of range size.
With the two functions now taking aligned arguments, further work most plausibly extends coverage to more EIA endpoints or response shapes. The entries name no specific target.
rfm computes recency, frequency and monetary segmentation for customer analytics in R. The feature surface was set early: 0.1.0 shipped a Shiny app and customer-level input, 0.2.0 added default segments and median statistics, 0.2.1 added user-specified score thresholds and returnable plot objects. Then nothing for nearly six years. Version 0.4.0 in April 2026 fixes a missing-column error and a customer id fault, and moves plotly and gganimate from Suggests to Imports.
The 0.4.0 release says more about maintenance posture than about product direction — the version jump past 0.3.x with only two bug fixes and a dependency reshuffle suggests a package being brought back to a releasable state rather than resuming development. Promoting plotly and gganimate to Imports makes the visualization stack mandatory, which is a heavier install in exchange for a simpler code path. The core RFM computation itself has not changed in this window.
The entries show a package returning from dormancy rather than pursuing a roadmap, so further small fixes are more likely than new segmentation capability.
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 eiaapi or rfm.
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
SEM reporting helpers converging on APA output, one CRAN resubmission at a time.
A raster-to-terra migration is the only readable change in a feed of merge notes.
A nycflights13 generator whose recent work is all about the data being right.
Conditional density and log-likelihood fill out a vine copula regression package.
A drop-in string API for base R, kept alive by upstream check failures.
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. eiaapi and rfm 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. eiaapi and rfm 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 eiaapi alternatives in Analytics are ranked by recent ship velocity. Browse the "eiaapi alternatives" section above for the current picks, or visit /alternatives/eiaapi for the full list with editorial commentary on each.
Top rfm alternatives in Analytics are ranked by recent ship velocity. Browse the "rfm alternatives" section above for the current picks, or visit /alternatives/rfm for the full list with editorial commentary on each.