sdv-dev/CTGAN

Health v2 · maintenance only

Flags: no_license

Adoption not part of the score

1569 stars · 335 forks observed · 2026-09-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

CTGAN is a Python library of deep learning based synthetic data generators for single-table tabular data, implementing the CTGAN conditional GAN and TVAE models. It learns from real datasets and generates high-fidelity synthetic rows for testing, privacy, and ML workflows.

Use cases

• generate synthetic tabular data from a csv
• create fake training data with a gan
• augment a small dataset with synthetic rows
• generate privacy-safe test data for a database table
• train a model on synthetic tabular data
• balance imbalanced tabular datasets with synthetic samples

When to choose

• you need synthetic single-table data with realistic column distributions and correlations
• you want a Python API for CTGAN or TVAE models
• you need to generate data for testing, demos, or ML augmentation

When to avoid

• you need synthetic data for relational or multi-table schemas - use the full SDV library instead
• you need image, text, or time-series generation
• you require production-grade stability - the library is labeled Pre-Alpha

Facets

library · maturity active

machine-learning deep-learning data-generation machine-learning data-science artificial-intelligence python synthetic-data gan tabular-data tvae generative-models

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markdown · JSON · MCP: product_card(name="sdv-dev/CTGAN")