rjdqa
rjdqa keeps refining one screen: the seasonal adjustment quality dashboard
A side-by-side editorial comparison of epiflows and tidypolars — release velocity, themes, recent moves, and the top alternatives to consider.
epiflows has shipped four releases in eight years, none of which changed the code.
epiflows predicts the spread of infectious disease along population flows between locations, and it is effectively dormant. The whole visible history spans 2018 to 2026 in four entries: the first CRAN release, a Zenodo archival tag, a Roxygen patch whose notes state the functionality is unchanged, and a 2026 release replacing deprecated ggplot2 and tibble calls. No entry describes new epidemiological capability.
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.
epiflows predicts the spread of infectious disease along population flows between locations, and it is effectively dormant. The whole visible history spans 2018 to 2026 in four entries: the first CRAN release, a Zenodo archival tag, a Roxygen patch whose notes state the functionality is unchanged, and a 2026 release replacing deprecated ggplot2 and tibble calls. No entry describes new epidemiological capability.
The package is being kept installable rather than developed. The one recent release is dependency maintenance contributed from outside, which is the pattern for RECON-era epidemiology packages that have outlived their original project funding. Two separate entries are both labelled version 0.2.1, so even the version history is not a reliable guide to what changed.
Any further releases will most likely be more deprecation cleanup to keep the package on CRAN; there is nothing in the record suggesting active development has resumed.
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 epiflows or tidypolars.
rjdqa keeps refining one screen: the seasonal adjustment quality dashboard
epikit narrows to field-epidemiology helpers, handing proportions to a sibling package
SimInf 10.0 turns an epidemic simulator into a tool that fits models to real time series
A young package porting Stata's egen row-wise helpers to the tidyverse, one function per release
A statistician's personal toolbox, growing one plotting utility at a time
R/qtl is in pure custodial mode: every recent release answers a compiler, not a user
See all epiflows alternatives → · See all tidypolars alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r — within Analytics. epiflows and tidypolars 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. epiflows and tidypolars 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.
Top epiflows alternatives in Analytics are ranked by recent ship velocity. Browse the "epiflows alternatives" section above for the current picks, or visit /alternatives/epiflows-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.