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FakeDataR

Privacy-Preserving Synthetic Data for 'LLM' Workflows

v0.2.2 · Oct 6, 2025 · MIT + file LICENSE

Description

Generate privacy-preserving synthetic datasets that mirror structure, types, factor levels, and missingness; export bundles for 'LLM' workflows (data plus 'JSON' schema and guidance); and build fake data directly from 'SQL' database tables without reading real rows. Methods are related to approaches in Nowok, Raab and Dibben (2016) <doi:10.32614/RJ-2016-019> and the foundation-model overview by Bommasani et al. (2021) <doi:10.48550/arXiv.2108.07258>.

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r-devel-linux-x86_64-debian-clang OK
r-devel-linux-x86_64-debian-gcc OK
r-devel-linux-x86_64-fedora-clang OK
r-devel-linux-x86_64-fedora-gcc OK
r-devel-windows-x86_64 OK
r-oldrel-macos-arm64 OK
r-oldrel-macos-x86_64 OK
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Check History

OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026

Dependency Network

Dependencies Reverse dependencies dplyr jsonlite zip FakeDataR

Version History

1 tracked
new 0.2.2 Mar 10, 2026

R Observatory began tracking this package on Mar 10, 2026; it first appeared on CRAN Oct 6, 2025. Releases before tracking aren’t shown.