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moderndive vs trendseries

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

Shared themes:r-package

moderndive vs trendseries: at a glance

Featuremoderndivetrendseries
SectorAnalyticsAnalytics
Velocity score2.53.8
Sparks · 30d01
Top themesstatistics-education, webr, regression, r-packagetime-series, econometrics, r-package, seasonal-decomposition
Last editorial update1h ago42m ago
WebsiteVisit →Visit →

What is moderndive?

The ModernDive teaching package learns to render inside the browser that runs its own textbook

moderndive supplies the datasets, regression helpers and ggplot geoms used by the ModernDive introductory statistics textbook. Its release history is mostly dataset accumulation — much of it contributed by students in batches — punctuated by occasional function work. The latest release is different: it fixes View() so it renders inside webR, the in-browser R that powers the book's live exercises, and reworks the regression helpers to survive in-formula transformations.

Read the full moderndive trajectory →

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.

Read the full trendseries trajectory →

moderndive vs trendseries: editorial side-by-side

M
moderndive
ANALYTICS
2.5

The ModernDive teaching package learns to render inside the browser that runs its own textbook

◆ Current state

moderndive supplies the datasets, regression helpers and ggplot geoms used by the ModernDive introductory statistics textbook. Its release history is mostly dataset accumulation — much of it contributed by students in batches — punctuated by occasional function work. The latest release is different: it fixes View() so it renders inside webR, the in-browser R that powers the book's live exercises, and reworks the regression helpers to survive in-formula transformations.

◆ Where it's heading

The package is following the textbook's second edition into the browser. webR has no pandoc, so the DT htmlwidget path the package relied on cannot produce the self-contained HTML the notebook cell needs, and the auto-print path was gated behind interactive() being false — meaning students working through the live exercises saw an explanatory message where a table should have been. Building a static HTML table and pushing it through webR's viewer hook is a small change with a direct effect on whether the book's interactive mode works at all.

◆ Prediction

With the book's v2 datasets landed and the browser rendering path fixed, the remaining friction is most likely in other functions that assume a desktop R session.

T
trendseries
ANALYTICS
3.8

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 moderndive 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 moderndive or trendseries.

See all moderndive alternatives → · See all trendseries alternatives →

Recent activity from moderndive and trendseries

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

  1. 12d agomoderndiveView() renders in webR; regression helpers survive formula transforms
  2. 15d agotrendseriesDecomposition becomes a first-class operation, five methods deep
  3. 3mo agotrendseriesMulti-column trends and economically grounded UCM defaults
  4. 10mo agotrendseriesFirst production release with 21 trend extraction methods
  5. 1y agomoderndiveDatasets and tidy_summary() for the second edition
  6. 2y agomoderndiveAlmond and flight datasets for the inference chapters
  7. 4y agomoderndiveTen student-curated teaching datasets
  8. 4y agomoderndiveAlaska flights subset added
  9. 5y agomoderndiveCleaner regression tables and an explicit conf.level argument

Frequently asked questions

What is the difference between moderndive 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 moderndive 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 moderndive?

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