mice
mice can finally predict, not just estimate, from multiply imputed data.
A side-by-side editorial comparison of surveytidy and tidyprompt — release velocity, themes, recent moves, and the top alternatives to consider.
surveytidy taught every dplyr verb to operate on a whole collection of surveys at once.
surveytidy is the tidyverse-facing half of a two-package survey stack, wrapping survey design objects from surveycore so filter, mutate, select and the rest work on them while carrying variable labels, value labels and a transformation log alongside the data. The May release extended that verb surface to survey_collection, the abstraction surveycore uses to hold several surveys as one object, so a pipeline written once dispatches across every member.
An R prompting framework hands its provider plumbing to ellmer and inherits MCP tools
tidyprompt composes LLM prompts out of stackable 'prompt wraps' — answer_as_json(), answer_as_category(), answer_using_tools() — and validates what comes back. Its recent history is one decision: stop maintaining a provider layer. llm_provider_ellmer() arrived experimental, then became the path through which structured output, tool calling and streaming are done natively. The newest release adds dataframe and numeric extraction wraps and lets send_prompt() take an ellmer chat object directly.
surveytidy is the tidyverse-facing half of a two-package survey stack, wrapping survey design objects from surveycore so filter, mutate, select and the rest work on them while carrying variable labels, value labels and a transformation log alongside the data. The May release extended that verb surface to survey_collection, the abstraction surveycore uses to hold several surveys as one object, so a pipeline written once dispatches across every member.
The package is being built in two layers that arrive in order: vector-level transformations first, structural dispatch second. The make_* family in 0.4.0 handles the recoding that survey work actually consists of — labelled to factor, multi-level to dichotomous, scale reversal, valence flipping — with value labels propagating automatically. Collection support then applies data-masking, tidyselect, grouping, slicing and collapsing verbs per survey, with joins explicitly refused and a typed message reporting which surveys were skipped. Metadata fidelity is the recurring bug source: labels surviving across(), stale labels left behind by recoding, the transformation log keeping up with what the verbs did.
Joins are the one verb family that errors on collections, with users directed to join before constructing the collection, so that restriction is the clearest outstanding gap. The re-export of surveycore's collection constructors suggests the package is positioning itself as the single import users need, which points toward more re-exports as surveycore's stable API settles.
tidyprompt composes LLM prompts out of stackable 'prompt wraps' — answer_as_json(), answer_as_category(), answer_using_tools() — and validates what comes back. Its recent history is one decision: stop maintaining a provider layer. llm_provider_ellmer() arrived experimental, then became the path through which structured output, tool calling and streaming are done natively. The newest release adds dataframe and numeric extraction wraps and lets send_prompt() take an ellmer chat object directly.
Two lines run together. One is catalogue growth — every release adds a wrap for another answer shape. The other is consolidation onto ellmer, and that is where the leverage is: because ellmer tool definitions are what mcptools::mcp_tools() returns, tidyprompt gained access to Model Context Protocol servers without writing an MCP client. Its own Gemini provider is already marked superseded. Note the feed's stamps lie — 0.1.0, 0.2.0 and 0.3.0 were all published within two hours of each other in reverse version order.
The remaining first-party providers are the obvious next thing to fold in: the Gemini one is already superseded, and the Ollama and OpenAI providers carry the same duplicated plumbing. Expect the wrap catalogue to keep growing on top of an increasingly ellmer-only base.
Other Infra & APIs 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 surveytidy or tidyprompt.
mice can finally predict, not just estimate, from multiply imputed data.
A market-microstructure toolkit that keeps adding estimators as the papers land.
A vowel-analysis package trimming dependencies after an email address got it archived.
The R half of the EMU speech database system, fixing what was quietly broken.
A Bayesian model-averaging package spending its 2.0 on memory, not methods.
tidyplots keeps rebuilding its own foundations rather than layering around them.
See all surveytidy alternatives → · See all tidyprompt alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. surveytidy and tidyprompt 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. surveytidy and tidyprompt 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 Infra & APIs products to evaluate alongside.
Top surveytidy alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "surveytidy alternatives" section above for the current picks, or visit /alternatives/surveytidy for the full list with editorial commentary on each.
Top tidyprompt alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "tidyprompt alternatives" section above for the current picks, or visit /alternatives/tidyprompt for the full list with editorial commentary on each.