eds-scikit 0.1.7

eds-scikit is a Python library providing tools to

eds-scikit is a tool to assist data scientists working on the AP-HP's Clinical Data Warehouse. It is specifically targeted for OMOP-standardized data. It main goals are to:

• Ease access and analysis of data
• Allow a better transfer of knowledge between projects
• Improve research reproducibility

Development

This library is developed and maintained by the core team of AP-HP’s Clinical Data Warehouse (EDS) with the strong support of Inria's SODA team.

How to use

Please check the online documentation for more informations. You will find

• Detailed explanation of the project goal and working principles
• A complete API documentation
• Various Jupyter Notebooks describing how to use various functionnalities of eds-scikit
• And more !

Requirements

eds-scikit stands on the shoulders of Spark 2.4 which requires:

• Python ~3.7.1
• Java 8

Installation

You can install eds-scikit via pip:

pip install "eds-scikit[aphp]"

:warning: If you get an an error during installation, please try downgrading pip via pip install -U "pip<23" before install eds-scikit`

:warning: If you don't work in AP-HP's ecosystem (EDS), please install via:

pip install eds-scikit

You can now import the library via

import eds_scikit

Contributing

• You want to help on the project ?
• You developped an interesting feature and you think it could benefit other by being integrated in the library ?
• You found a bug ?
• You have a question about the library ?
• ...

Please check our contributing guidelines.

Citation

If you use eds-scikit, please cite us as below.

@misc{eds-scikit,
    author = {Petit-Jean, Thomas and Remaki, Adam and Maladière, Vincent and Varoquaux, Gaël and Bey, Romain},
    doi = {10.5281/zenodo.7401549},
    title = {eds-scikit: data analysis on OMOP databases},
    url = {https://github.com/aphp/eds-scikit}
}

Acknowledgment

We would like to thank the following funders:

• Assistance Publique – Hôpitaux de Paris
• AP-HP Foundation
• Inria