OHPL
A 2017 chemometrics method frozen in place, visited only when CRAN changes its documentation rules.
A side-by-side editorial comparison of clinify and tidypolars — release velocity, themes, recent moves, and the top alternatives to consider.
Clinical-table typesetting for R, closing the gap between R output and regulatory Word documents
clinify renders clinical trial tables into Word documents through {officer}, aiming at the layout conventions regulatory submissions expect. 0.4.0 is the current CRAN release and folds in an unreleased 0.3.1. The recent work is almost entirely about header and spacing control: which adjacent header cells merge, where the rule under a spanner starts and stops, and how much vertical space sits above, below and between header rows and the table body.
tidypolars is grinding toward complete dplyr coverage, one supported function at a time
tidypolars lets you write dplyr and tidyr syntax against Polars DataFrames and LazyFrames. Its releases follow a fixed shape: raise the required polars version, add a handful of newly supported R functions and arguments, fix places where behaviour diverges from dplyr. Recent additions run from %notin% and as.integer() to .before/.after in mutate() and time zone handling in datetime parsing. Cadence is roughly every six to ten weeks and has not varied.
clinify renders clinical trial tables into Word documents through {officer}, aiming at the layout conventions regulatory submissions expect. 0.4.0 is the current CRAN release and folds in an unreleased 0.3.1. The recent work is almost entirely about header and spacing control: which adjacent header cells merge, where the rule under a spanner starts and stops, and how much vertical space sits above, below and between header rows and the table body.
The package is moving from producing a correct table toward producing one that survives an organisation's house style. 0.4.0's additions are all written to hold under a customised `clinify_table_default()` — `clin_spanner_rule()` draws after the default styling function so it persists when a house style clears the borders it started from, and takes an `officer::fp_border()` or `FALSE` so a style can decline the rule entirely. The earlier 0.3.0 line did the structural work, introducing `clindoc()` document objects that accept multiple tables plus automatic pagination.
Expect continued refinement of layout primitives that follow the table rather than fixed column numbers, since both new 0.4.0 functions were built specifically to track spanners and headers as a layout changes. The entries do not indicate a move beyond Word output.
tidypolars lets you write dplyr and tidyr syntax against Polars DataFrames and LazyFrames. Its releases follow a fixed shape: raise the required polars version, add a handful of newly supported R functions and arguments, fix places where behaviour diverges from dplyr. Recent additions run from %notin% and as.integer() to .before/.after in mutate() and time zone handling in datetime parsing. Cadence is roughly every six to ten weeks and has not varied.
Coverage is the whole strategy, and the target has been widening from dplyr into tidyr — unnest_longer_polars(), separate_longer_delim_polars() and separate_longer_position_polars() bring list-column and string-splitting verbs that have no Polars-idiomatic equivalent in the tidyverse dialect. The other consistent thread is fidelity: distinct() dropping unselected columns, summarize() dropping the last group, relocate() honouring tidy-select helpers, NULL in mutate() behaving as dplyr does. Each of these is a small breaking change made to match the reference rather than to differ from it.
The pattern of tracking the polars floor upward every release and following tidyverse changes closely — .by in fill() arrived when tidyr 1.3.2 shipped it — suggests the next releases continue mirroring new dplyr and tidyr arguments rather than adding a distinct capability.
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 clinify or tidypolars.
A 2017 chemometrics method frozen in place, visited only when CRAN changes its documentation rules.
A fast dplyr stand-in that keeps finding new places to skip work entirely.
Belgium's invasive-species indicator toolkit is in steady refinement, one plotting edge case at a time.
The ICES stock assessment client took upload away in 2024 and spent two years giving it back.
A discrete global grid generator grew cell traversal and became a usable spatial index.
Community ecology's standard toolkit is retiring the functions a generation of scripts was built on.
See all clinify alternatives → · See all tidypolars alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. clinify 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. clinify 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.
Top clinify alternatives in Analytics are ranked by recent ship velocity. Browse the "clinify alternatives" section above for the current picks, or visit /alternatives/clinify-r for the full list with editorial commentary on each.
Top tidypolars alternatives in Analytics are ranked by recent ship velocity. Browse the "tidypolars alternatives" section above for the current picks, or visit /alternatives/tidypolars for the full list with editorial commentary on each.