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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


pip install lifelines


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 discussion 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


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

  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


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

  Development blog <>
  Citing lifelines <Citing lifelines>
  Support lifelines <>

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

  Discussion forum <>
  Create a GitHub issue <>

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