HydroPortailStats
France's national flood statistics, ported out of Fortran and into R.
A side-by-side editorial comparison of dataSDA and estimatr — release velocity, themes, recent moves, and the top alternatives to consider.
dataSDA grew from a dataset collection into a symbolic-data conversion toolkit.
The package now carries 105 documented datasets in interval, histogram, modal, and mixed symbolic formats, drawn from other R packages, the Billard and Diday textbooks, and public sources such as the Portuguese air quality network. Alongside the data it has accumulated conversion functions between the MM, RSDA, iGAP, SODAS, and ARRAY representations, CSV read and write support, and a keyword search over the catalogue.
Fast design-based estimators for experiments, coasting on CRAN patches.
estimatr provides the design-based regression estimators the DeclareDesign ecosystem is built on — robust and cluster-robust standard errors, blocked and clustered randomization inference — implemented for speed rather than generality. The last three releases carry no substantive notes: each is a merge commit for a CRAN patch, one of them accompanied by a typo fix.
The package now carries 105 documented datasets in interval, histogram, modal, and mixed symbolic formats, drawn from other R packages, the Billard and Diday textbooks, and public sources such as the Portuguese air quality network. Alongside the data it has accumulated conversion functions between the MM, RSDA, iGAP, SODAS, and ARRAY representations, CSV read and write support, and a keyword search over the catalogue.
The arc across this window runs from cataloguing to tooling. Early releases added datasets and then spent two consecutive releases fixing format documentation across all 105 of them. Later releases shift to functions: format converters, symbolic CSV I/O, and most recently a diagnostic that flags zero-width intervals before they reach tools that divide by interval width. That last addition is the clearest signal of intent — the package is starting to guard the analyses downstream of it, not just supply inputs.
Expect further validation helpers in the mould of the zero-width check, since interval data has several degenerate shapes that break downstream methods silently.
estimatr provides the design-based regression estimators the DeclareDesign ecosystem is built on — robust and cluster-robust standard errors, blocked and clustered randomization inference — implemented for speed rather than generality. The last three releases carry no substantive notes: each is a merge commit for a CRAN patch, one of them accompanied by a typo fix.
Direction cannot be read from this feed. The release notes are unedited merge-commit messages, so the only signal is cadence — roughly annual, each release framed as a CRAN patch rather than as feature work. That pattern is consistent with a package whose estimators are considered finished and which now moves only when CRAN policy requires it.
On the evidence here the next release is another CRAN compliance patch, but the notes are too thin to support a confident read of what the maintainers are actually working on.
Other Infra & APIs 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 dataSDA or estimatr.
France's national flood statistics, ported out of Fortran and into R.
Sign, zero and narrative restrictions brought into the bsvars ecosystem.
The grammar of uncertainty visualization, now drawing the uncertainty in its own estimates.
IP address vectors for R that hit 1.0 and then went quiet.
A column-key toolkit for stitching decades of ecological field data into one table.
Microsoft's automated forecasting framework, still mostly a one-maintainer effort.
See all dataSDA alternatives → · See all estimatr alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Infra & APIs. dataSDA 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. dataSDA 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 Infra & APIs products to evaluate alongside.
Top dataSDA alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "dataSDA alternatives" section above for the current picks, or visit /alternatives/datasda for the full list with editorial commentary on each.
Top estimatr alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "estimatr alternatives" section above for the current picks, or visit /alternatives/estimatr for the full list with editorial commentary on each.