Prince

Prince is a Python library for multivariate exploratory data analysis in Python. It includes a variety of methods for summarizing tabular data, including principal component analysis and correspondence analysis. Prince provides efficient implementations, using a scikit-learn API.

Methods

flowchart TD cat?(Categorical data?) --> |"✅"| num_too?(Numerical data too?) num_too? --> |"✅"| FAMD num_too? --> |"❌"| multiple_cat?(More than two columns?) multiple_cat? --> |"✅"| MCA multiple_cat? --> |"❌"| CA cat? --> |"❌"| groups?(Groups of columns?) groups? --> |"✅"| MFA groups? --> |"❌"| shapes?(Analysing shapes?) shapes? --> |"✅"| GPA shapes? --> |"❌"| PCA

Installation

pip install prince

🎨 Prince uses Altair for making charts.

Correctness

Prince is tested against scikit-learn and FactoMineR. For the latter, rpy2 is used to run code in R, and convert the results to Python, which allows running automated tests. See more in the tests directory.

Citation

Please use this citation if you use this software as part of a scientific publication.

@software{Halford_Prince,
    author = {Halford, Max},
    license = {MIT},
    title = {{Prince}},
    url = {https://github.com/MaxHalford/prince}
}

About

I made Prince when I was at university, back in 2016. We used FactoMineR extensively in our labs, and so my initial motivation was to provide the same features for Python. I’ve had very little time over the years to maintain this package. I spent a significant of time in 2022 to revamp the entire package. Prince has now been downloaded over 2 million times.

License

The MIT License (MIT). Please see the license file for more information.