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bagyo vs tglkmeans

A side-by-side editorial comparison of bagyo and tglkmeans — release velocity, themes, recent moves, and the top alternatives to consider.

bagyo vs tglkmeans: at a glance

Featurebagyotglkmeans
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesopen data, tropical cyclones, philippines, data packager-package, clustering, missing-data, correctness
Last editorial update42m ago2h ago
WebsiteVisit →Visit →

What is bagyo?

bagyo reached CRAN as a Philippine tropical cyclone dataset, with its tags stamped out of order.

A data package distributing Philippine Area of Responsibility tropical cyclone records, developed through 2024 pre-releases and accepted by CRAN in early 2026. The substantive release is v0.2.0: 2021 and 2022 typhoon data added, an unexported helper for downloading cyclone reports, CITATION.cff, an R 4.1 dependency for the base pipe, and a full pass over vignettes, tests and README. The v0.1.1 tag announcing the first CRAN release carries no content and is stamped two hours after v0.2.0.

Read the full bagyo trajectory →

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.

Read the full tglkmeans trajectory →

bagyo vs tglkmeans: editorial side-by-side

B
bagyo
ANALYTICS
0.0

bagyo reached CRAN as a Philippine tropical cyclone dataset, with its tags stamped out of order.

◆ Current state

A data package distributing Philippine Area of Responsibility tropical cyclone records, developed through 2024 pre-releases and accepted by CRAN in early 2026. The substantive release is v0.2.0: 2021 and 2022 typhoon data added, an unexported helper for downloading cyclone reports, CITATION.cff, an R 4.1 dependency for the base pipe, and a full pass over vignettes, tests and README. The v0.1.1 tag announcing the first CRAN release carries no content and is stamped two hours after v0.2.0.

◆ Where it's heading

The package is establishing itself as a citable, yearly-updated dataset rather than a one-off scrape — the download helper and the '2022 data and general yearly upkeep' commit both point at a recurring refresh, and the CRAN DOI and CITATION file exist so the data can be cited in papers. It sits alongside the same maintainer's other public-health and survey data packages, which received matching repository upkeep in the same month.

◆ Prediction

Expect an annual data release adding the next typhoon season, since that is the only recurring change in the history and the download helper was written to support it.

T
tglkmeans
ANALYTICS
0.0

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 bagyo 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 bagyo or tglkmeans.

See all bagyo alternatives → · See all tglkmeans alternatives →

Recent activity from bagyo and tglkmeans

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 2mo agotglkmeansSpearman metric no longer ranks missing values as the largest
  2. 7mo agobagyobagyo v0.1.1
  3. 7mo agobagyo2021 and 2022 typhoon data added
  4. 2y agobagyoPre-release for Zenodo archiving
  5. 2y agobagyoInitial pre-release
  6. 2y agotglkmeansFixes corrupted cluster ids and dropped dimnames
  7. 2y agotglkmeansAdds downsample_matrix() for count matrices
  8. 2y agotglkmeansBreaking: id_column defaults to FALSE, switches to R's RNG

Frequently asked questions

What is the difference between bagyo and tglkmeans?

They serve adjacent needs but don't currently overlap on shipped themes. bagyo and tglkmeans 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.

Is bagyo better than tglkmeans?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. bagyo and tglkmeans 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.

What are the best alternatives to bagyo?

Top bagyo alternatives in Analytics are ranked by recent ship velocity. Browse the "bagyo alternatives" section above for the current picks, or visit /alternatives/bagyo 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.