Survival analysis in Python, including Kaplan Meier, Nelson Aalen and regression
Project description
What is survival analysis and why should I learn it? Survival analysis was originally developed and applied heavily by the actuarial and medical community. Its purpose was to answer why do events occur now versus later under uncertainty (where events might refer to deaths, disease remission, etc.). This is great for researchers who are interested in measuring lifetimes: they can answer questions like what factors might influence deaths?
But outside of medicine and actuarial science, there are many other interesting and exciting applications of this lesser-known technique, for example: - SaaS providers are interested in measuring customer lifetimes, or time to first behaviours - sociologists are interested in measuring political parties’ lifetimes, or relationships, or marriages - analysing Godwin’s law in Reddit comments - A/B tests to determine how long it takes different groups to perform an action.
lifelines is a pure Python implementation of the best parts of survival analysis. We’d love to hear if you are using lifelines, please leave an Issue and let us know your thoughts on the library.
Installation:
Dependencies:
The usual Python data stack: NumPy, SciPy, Pandas (a modern version please). Matplotlib is optional (as of 0.6.0+).
Installing
You can install lifelines using
pip install lifelines
Or getting the bleeding edge version with:
pip install --upgrade --no-deps git+https://github.com/CamDavidsonPilon/lifelines.git
from the command line.
Installation Issues?
See the common problems/solutions for installing lifelines.
Running the tests
You can optionally run the test suite after install with
py.test
lifelines Documentation and an intro to survival analysis
If you are new to survival analysis, wondering why it is useful, or are interested in lifelines examples and syntax, please check out the Documentation and Tutorials page
Contacting
There is a Gitter channel available. The main author, Cam Davidson-Pilon, is also available for contact on email and twitter.
Citing lifelines
You can use this badge below to generate a DOI and reference text for the latest related version of lifelines:
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distributions
File details
Details for the file lifelines-0.14.1.tar.gz.
File metadata
- Download URL: lifelines-0.14.1.tar.gz
- Upload date:
- Size: 217.7 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | ea735d8069f3574a92417566c00e1112186d70e41f70bc0aaea43bacfa3aac7d |
|
| MD5 | 87ef530d9206d635c34aae1f97b18d85 |
|
| BLAKE2b-256 | 1845c014cc444936599e273ece58f0ffccbffa60c234a4ad2e9bf33121667084 |
File details
Details for the file lifelines-0.14.1-py3-none-any.whl.
File metadata
- Download URL: lifelines-0.14.1-py3-none-any.whl
- Upload date:
- Size: 215.0 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 8d7ee639831d43bdcedab912c221fc30f5f6dd7852b15ffc60d4680dedd3f7af |
|
| MD5 | cc852b8eb6925a42fed23e72278c7fbd |
|
| BLAKE2b-256 | afd1c76ccbad490f34c78736e74448d7278b40ec85de92a74a0ecfddcca2c5d7 |
File details
Details for the file lifelines-0.14.1-py2.py3-none-any.whl.
File metadata
- Download URL: lifelines-0.14.1-py2.py3-none-any.whl
- Upload date:
- Size: 215.0 kB
- Tags: Python 2, Python 3
- Uploaded using Trusted Publishing? No
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 27f6f6eed01077494f17e617a060f22b522ba4979448bde492cd7d19cff9fde6 |
|
| MD5 | 295979968a9cc70b41226fb3fab05733 |
|
| BLAKE2b-256 | c72d9d8f4c88a7df39434ffc066282f36df38417ca2ebd0823436b62d14df1a2 |
