{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/7"}],"enrichment":{"capability":"Copulas models multivariate statistical distributions and generates synthetic tabular data that preserves the statistical properties of the original dataset using copula functions.","skillfed_tags":["synthetic-data","statistical-modeling","data-generation"],"use_cases":["Generate privacy-preserving synthetic datasets for testing and development without exposing real customer or sensitive data","Create balanced training datasets for machine learning by sampling from learned multivariate distributions","Augment small datasets by learning their statistical structure and generating additional synthetic records","Validate data pipelines and analytics by producing synthetic data with known statistical properties","Compare real versus synthetic data distributions visually to verify model quality before deployment"],"what_it_does":"Copulas is a Python library for learning multivariate distributions from numerical data and generating synthetic data that follows the same statistical patterns. You provide a table of real data, fit a copula model (choosing from options like Gaussian Copula, Vine Copulas, or Archimedian Copulas), and then sample new synthetic records that preserve the correlations and marginal distributions of the original. The library integrates with numpy, pandas, scipy for computation and plotly for visualization, allowing you to compare real and synthetic data side-by-side in 1D, 2D, and 3D plots.\n\nThe package is part of the Synthetic Data Vault Project and targets developers and data engineers building synthetic data pipelines. It exposes the learned model parameters for inspection and tuning, making it suitable for both exploratory work and production use where you need control over the generation process. The codebase is actively maintained, supports Python 3.9 through 3.14, and has no known security vulnerabilities.","worth_installing":"Yes, with conditions. The package is actively maintained, has low install friction, and solves a real need for synthetic tabular data generation. However, the BUSL-1.1 license restricts commercial use until a future date\u2014verify the license terms against your use case before committing. The pre-alpha development status suggests the API may change; for production use, pin the version and monitor releases."},"id":"copulas","links":{"html":"https://skillfed.io/packages/copulas","md":"https://skillfed.io/packages/copulas.md","pypi":"https://pypi.org/project/copulas/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-02-05","license_spdx":"BUSL-1.1","license_treatment":"unclear","name":"copulas","python_support":"supports_current","summary":"Create tabular synthetic data using copulas-based modeling."},"popularity":{"monthly_downloads":201903,"position":9656,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.14.1"}