FakeDataR
0.2.2Privacy-Preserving Synthetic Data for 'LLM' Workflows
Overview
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.
Install
Health
- OK2026-08-0513 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 67%
- Documented parameters
- 97%
- Return-value docs
- 100%
- References docs
- 0%
Downloads
Repository
Repository practices
5 development-tooling and community-health practices detected across 5 families in the upstream repository
Checks run against github.com/zobaer09/fakedatar on 2026-08-16.
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Dependencies
Nothing depends on this yet.
Code & Tests
People & History
1 release. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- 0.2.2Latest2026-03-10 · current release
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2025-10-06
- Total releases
- 1 / 1 yrs
- License
- MIT + file LICENSE OSI
- Download size
- 62 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("FakeDataR")This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.
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