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Comparison · Analytics
r-owidapi vs tglkmeans
A side-by-side editorial comparison of r-owidapi and tglkmeans — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
r-owidapi vs tglkmeans: at a glance
What is r-owidapi?
The R client for Our World in Data found its search had been reading a tenth of the catalog.
owidapi is a small R client for Our World in Data, covering chart data retrieval, metadata, the full chart catalog, and search over it, with experimental Shiny output helpers. It is three releases old and the most recent one is almost entirely repair: the catalog function was silently truncating at 1000 rows because of a Datasette row cap, which meant search had been operating on a fraction of what exists.
What is tglkmeans?
A k-means implementation that just told users their Spearman clustering on missing data was wrong
tglkmeans is a multi-core k-means implementation with seeding, aimed at single-cell and other large matrix workloads. Version 0.4.0 flipped the id_column default and moved to R's random number generator, 0.5.x added count-matrix downsampling and fixed id handling, and 0.6.3 in May 2026 is a correctness release: Spearman distance was ranking missing values as the largest value instead of dropping them, and predict_tgl_kmeans() with Euclidean distance did not reproduce the training metric when a cluster center had a missing dimension.
r-owidapi vs tglkmeans: editorial side-by-side
r-owidapi
2.5ANALYTICS
The R client for Our World in Data found its search had been reading a tenth of the catalog.
◆ Current state
owidapi is a small R client for Our World in Data, covering chart data retrieval, metadata, the full chart catalog, and search over it, with experimental Shiny output helpers. It is three releases old and the most recent one is almost entirely repair: the catalog function was silently truncating at 1000 rows because of a Datasette row cap, which meant search had been operating on a fraction of what exists.
◆ Where it's heading
Development is about making a thin wrapper trustworthy against an upstream that moves without notice. The truncation fix pages through the catalog properly; a separate fix stops the function breaking when Our World in Data dropped a column, by parsing typed columns only when present. Tests moved to mocked responses, with a small live suite retained purely to detect schema drift and skipped on CRAN — a sensible design for a package whose main risk is that the API changes shape rather than that the code is wrong. The user-facing surface has not grown since the initial release; the work is in defending it.
◆ Prediction
On this pattern the next release is likelier to be another upstream-compatibility fix than new functionality, with the schema-drift tests the mechanism that surfaces it.
tglkmeans
0.0ANALYTICS
A k-means implementation that just told users their Spearman clustering on missing data was wrong
◆ Current state
tglkmeans is a multi-core k-means implementation with seeding, aimed at single-cell and other large matrix workloads. Version 0.4.0 flipped the id_column default and moved to R's random number generator, 0.5.x added count-matrix downsampling and fixed id handling, and 0.6.3 in May 2026 is a correctness release: Spearman distance was ranking missing values as the largest value instead of dropping them, and predict_tgl_kmeans() with Euclidean distance did not reproduce the training metric when a cluster center had a missing dimension.
◆ Where it's heading
The package handles missing data across three distance metrics, and 0.6.3 shows those paths had drifted apart — Spearman behaved unlike Euclidean and Pearson, and prediction behaved unlike training. Both fixes change results on affected data, and the release notes are careful to bound exactly where: Spearman on data with NAs changes, complete data does not. Performance work runs alongside, with the dense per-thread vote matrix removed from the reassignment step.
◆ Prediction
With the metric paths now aligned on missing-value handling, further work is more likely to target the parallel reassignment internals than the distance semantics.
Alternatives to r-owidapi and tglkmeans
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 r-owidapi or tglkmeans.
gcube
gcube's recent releases are all packaging metadata, not simulation code
cubist
The R port of Quinlan's Cubist gets reproducibility fixes, not new modelling
ggstats
ggstats keeps widening what a coefficient or Likert plot can be
ecodive
ecodive rebuilt itself into a broad diversity-metric library, breaking as it went
simStateSpace
State-space data simulation for R, filled in one function at a time
See all r-owidapi alternatives → · See all tglkmeans alternatives →
Recent activity from r-owidapi and tglkmeans
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 20d agor-owidapiCatalog was silently capped at 1000 charts; now paged in full
- 2mo agotglkmeansSpearman metric no longer ranks missing values as the largest
- 1y agor-owidapiRequest logic consolidated, with graceful catalog errors
- 1y agor-owidapiFirst release: data, metadata, catalog and search
- 2y agotglkmeansFixes corrupted cluster ids and dropped dimnames
- 2y agotglkmeansAdds downsample_matrix() for count matrices
- 2y agotglkmeansBreaking: id_column defaults to FALSE, switches to R's RNG
Frequently asked questions
What is the difference between r-owidapi and tglkmeans?
Both compete on the same themes — r-package — within Analytics. r-owidapi 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.
Is r-owidapi better than tglkmeans?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. r-owidapi 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.
What are the best alternatives to r-owidapi?
Top r-owidapi alternatives in Analytics are ranked by recent ship velocity. Browse the "r-owidapi alternatives" section above for the current picks, or visit /alternatives/r-owidapi for the full list with editorial commentary on each.
What are the best alternatives to tglkmeans?
Top tglkmeans alternatives in Analytics are ranked by recent ship velocity. Browse the "tglkmeans alternatives" section above for the current picks, or visit /alternatives/tglkmeans for the full list with editorial commentary on each.