nflreadr
The nflverse data loader, whose releases are dictated by the NFL calendar and CRAN's archive policy
Comparison · Analytics
r-owidapi vs trendseries
A side-by-side editorial comparison of r-owidapi and trendseries — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
r-owidapi vs trendseries: 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 trendseries?
A trend-extraction toolkit grows a full decomposition engine, seasonal components and all.
trendseries extracts trends from economic time series through two pipe-friendly functions, backed by an unusually broad method set — Hodrick-Prescott in one- and two-sided variants, Baxter-King, Christiano-Fitzgerald, Hamilton regression, Beveridge-Nelson, unobserved components, plus the moving average and smoothing family. The 1.4 release adds decomposition proper: an exported decompose_series() that splits a series into trend, seasonal, and remainder across five methods and guarantees the components add back to the original values.
r-owidapi vs trendseries: 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.
trendseries
3.8ANALYTICS
A trend-extraction toolkit grows a full decomposition engine, seasonal components and all.
◆ Current state
trendseries extracts trends from economic time series through two pipe-friendly functions, backed by an unusually broad method set — Hodrick-Prescott in one- and two-sided variants, Baxter-King, Christiano-Fitzgerald, Hamilton regression, Beveridge-Nelson, unobserved components, plus the moving average and smoothing family. The 1.4 release adds decomposition proper: an exported decompose_series() that splits a series into trend, seasonal, and remainder across five methods and guarantees the components add back to the original values.
◆ Where it's heading
The package is moving from breadth of methods to rigour about what those methods produce. Recent work has been about defaults and guarantees rather than new filters: the unobserved components model now derives its signal-to-noise ratios from Hodrick-Prescott lambdas so the default output is economically interpretable, decomposition carries an exact additive identity, and a log transform gives a uniform multiplicative variant across every method. Naming is being tidied in the same spirit, with group_vars deprecated in favour of group_cols. Side-by-side method comparison — passing several methods and getting each one's components as separate columns — suggests an audience that treats method choice as a research question rather than a setting.
◆ Prediction
Expect the comparison and diagnostic side to keep developing, since the package now produces multiple decompositions of the same series and offers no ranking between them; the entries give no indication of new filters being queued.
Alternatives to r-owidapi and trendseries
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 trendseries.
susier
Fine-mapping workhorse susieR spends its releases hunting null-effect trimming bugs
UCell
A rank-based gene signature scorer that has grown by adapting to whatever object format single-cell R uses next
detectseparation
A diagnostic package that generalized past its own name, then learned to say which kind of separation it found
brglm2
A bias-reduction package reaches 1.0 by adding an estimator built for high-dimensional logistic regression
bayestools
The JAGS toolkit under RoBMA, shipping the standardization machinery its downstream rewrite needed
See all r-owidapi alternatives → · See all trendseries alternatives →
Recent activity from r-owidapi and trendseries
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 15d agotrendseriesDecomposition becomes a first-class operation, five methods deep ⚡
- 20d agor-owidapiCatalog was silently capped at 1000 charts; now paged in full
- 3mo agotrendseriesMulti-column trends and economically grounded UCM defaults
- 10mo agotrendseriesFirst production release with 21 trend extraction methods
- 1y agor-owidapiRequest logic consolidated, with graceful catalog errors
- 1y agor-owidapiFirst release: data, metadata, catalog and search
Frequently asked questions
What is the difference between r-owidapi and trendseries?
Both compete on the same themes — r-package — within Analytics. trendseries is currently shipping more aggressively (velocity 3.8 vs 2.5), with 1 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 trendseries?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. trendseries is currently shipping more aggressively (velocity 3.8 vs 2.5), with 1 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 trendseries?
Top trendseries alternatives in Analytics are ranked by recent ship velocity. Browse the "trendseries alternatives" section above for the current picks, or visit /alternatives/trendseries for the full list with editorial commentary on each.