nflreadr
The nflverse data loader, whose releases are dictated by the NFL calendar and CRAN's archive policy
Comparison · Analytics
ojoregex vs trendseries
A side-by-side editorial comparison of ojoregex and trendseries — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
ojoregex vs trendseries: at a glance
What is ojoregex?
Oklahoma's court-data nonprofit maintains the regex layer that turns charge text into categories.
ojoregex is Open Justice Oklahoma's pattern library for classifying criminal charge descriptions from court records — the unglamorous translation layer between free-text charge fields and analysable categories. Its entire release history reached this feed as four tags published within three minutes, so the feed order reflects a backfill rather than a shipping cadence. Release notes are merge references rather than descriptions, which limits how much can be read from the changelog alone.
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.
ojoregex vs trendseries: editorial side-by-side
ojoregex
0.0ANALYTICS
Oklahoma's court-data nonprofit maintains the regex layer that turns charge text into categories.
◆ Current state
ojoregex is Open Justice Oklahoma's pattern library for classifying criminal charge descriptions from court records — the unglamorous translation layer between free-text charge fields and analysable categories. Its entire release history reached this feed as four tags published within three minutes, so the feed order reflects a backfill rather than a shipping cadence. Release notes are merge references rather than descriptions, which limits how much can be read from the changelog alone.
◆ Where it's heading
What the notes do show is a package alternating between domain corrections and R tooling upkeep: a fix to property-crime matching in one release, dplyr select semantics in the next. That is the expected shape for a regex catalogue — accuracy work arrives as individual charge types get miscategorised in real analyses, and the rest is keeping the package installable against a moving tidyverse. Contributions come from a small internal team, and the vignette work referenced in the earliest tag suggests the pattern list doubles as documentation for analysts.
◆ Prediction
The visible pattern is incremental match fixes as charge types surface in use; the release notes carry too little detail to predict anything beyond that without reading the underlying pull requests.
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 ojoregex 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 ojoregex 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 ojoregex alternatives → · See all trendseries alternatives →
Recent activity from ojoregex and trendseries
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 15d agotrendseriesDecomposition becomes a first-class operation, five methods deep ⚡
- 1mo agoojoregexPatch for dplyr select semantics
- 1mo agoojoregexojoregex v0.10.0
- 1mo agoojoregexNamespace prefixes fixed, plus a property-crime match bug
- 1mo agoojoregexFirst tagged release, carrying the whole development history
- 3mo agotrendseriesMulti-column trends and economically grounded UCM defaults
- 10mo agotrendseriesFirst production release with 21 trend extraction methods
Frequently asked questions
What is the difference between ojoregex and trendseries?
Both compete on the same themes — r-package — within Analytics. trendseries is currently shipping more aggressively (velocity 3.8 vs 0.0), 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 ojoregex 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 0.0), 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 ojoregex?
Top ojoregex alternatives in Analytics are ranked by recent ship velocity. Browse the "ojoregex alternatives" section above for the current picks, or visit /alternatives/ojoregex 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.