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https://i.imgur.com/EOowdSD.png


lifelines

lifelines is a complete survival analysis library, written in pure Python. What benefits does lifelines have?

  • easy installation
  • internal plotting methods
  • simple and intuitive API
  • handles right, left and interval censored data
  • contains the most popular parametric, semi-parametric and non-parametric models

Installation

pip install lifelines

or

conda install -c conda-forge lifelines

Source code and issue tracker

Available on Github, CamDavidsonPilon/lifelines. Please report bugs, issues and feature extensions there. We also have Gitter channel available to discuss survival analysis and lifelines:

Citing lifelines

The following link will bring you to a page where you can find the latest citation for lifelines: Citation for lifelines

Documentation

.. toctree::
  :maxdepth: 1
  :caption: Quickstart & Intro

  Quickstart
  Survival Analysis intro

.. toctree::
  :maxdepth: 1
  :caption: Univariate Models

  Survival analysis with lifelines
  jupyter_notebooks/Piecewise Exponential Models and Creating Custom Models.ipynb
  jupyter_notebooks/Modelling time-lagged conversion rates.ipynb

.. toctree::
  :maxdepth: 1
  :caption: Regression Models

  Survival Regression
  jupyter_notebooks/Custom Regression Models.ipynb
  Compatibility with scikit-learn
  Time varying survival regression
  jupyter_notebooks/Proportional hazard assumption.ipynb

.. toctree::
  :maxdepth: 1
  :caption: Additional documentation

  References
  Examples

.. toctree::
  :maxdepth: 1
  :caption: About lifelines

  Changelog
  Development blog <https://dataorigami.net/blogs/napkin-folding/tagged/lifelines>
  Citing lifelines <https://doi.org/10.5281/zenodo.805993>

.. toctree::
  :maxdepth: 1
  :caption: Questions? Suggestions?

  Gitter channel <https://gitter.im/python-lifelines/Lobby>
  Create a GitHub issue <https://github.com/camdavidsonpilon/lifelines/issues>

.. toctree::
  :maxdepth: 1
  :caption: Developer Documentation

  Contributing
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