lifelines
lifelines: survival analysis in Python - Published in JOSS (2019)
Science Score: 100.0%
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 1 DOI reference(s) in JOSS metadata -
✓Academic publication links
Links to: zenodo.org -
✓Committers with academic emails
7 of 120 committers (5.8%) from academic institutions -
○Institutional organization owner
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✓JOSS paper metadata
Published in Journal of Open Source Software
Keywords
Keywords from Contributors
Scientific Fields
Repository
Survival analysis in Python
Basic Info
- Host: GitHub
- Owner: CamDavidsonPilon
- License: mit
- Language: Python
- Default Branch: master
- Homepage: lifelines.readthedocs.org
- Size: 43.1 MB
Statistics
- Stars: 2,487
- Watchers: 66
- Forks: 561
- Open Issues: 277
- Releases: 124
Topics
Metadata Files
README.md
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 survival analysis. For example: - SaaS providers are interested in measuring subscriber lifetimes, or time to some first action - inventory stock out is a censoring event for true "demand" of a good. - sociologists are interested in measuring political parties' lifetimes, or relationships, or marriages - 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.
Documentation and intro to survival analysis
If you are new to survival analysis, wondering why it is useful, or are interested in lifelines examples, API, and syntax, please read the Documentation and Tutorials page
Contact
- Start a conversation in our Discussions room.
- Some users have posted common questions at stats.stackexchange.com.
- Creating an issue in the Github repository.
Development
See our Contributing guidelines.
Owner
- Name: Cameron Davidson-Pilon
- Login: CamDavidsonPilon
- Kind: user
- Location: Waterloo, Canada
- Company: @Pioreactor
- Website: https://dataorigami.net
- Repositories: 90
- Profile: https://github.com/CamDavidsonPilon
CEO of Pioreactor. Former Director of Data Science @Shopify. Author of Bayesian Methods for Hackers and DataOrigami.
JOSS Publication
lifelines: survival analysis in Python
Authors
Independent researcher
Editor
Tania Allard
Tags
survival analysis reliability analysis maximum likelihoodCitation (CITATION.cff)
# YAML 1.2
---
authors:
-
family-names: "Davidson-Pilon"
given-names: Cameron
orcid: "https://orcid.org/0000-0003-1794-9143"
cff-version: "1.1.0"
doi: "https://doi.org/10.21105/joss.01317"
license: MIT
message: "If you use this software, please cite it using these metadata."
repository-code: "https://github.com/camDavidsonPilon/lifelines"
title: lifelines, survival analysis in Python
...
GitHub Events
Total
- Create event: 2
- Release event: 1
- Issues event: 16
- Watch event: 124
- Delete event: 1
- Issue comment event: 34
- Push event: 4
- Pull request event: 4
- Fork event: 13
Last Year
- Create event: 2
- Release event: 1
- Issues event: 16
- Watch event: 124
- Delete event: 1
- Issue comment event: 34
- Push event: 4
- Pull request event: 4
- Fork event: 13
Committers
Last synced: 5 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| CamDavidsonPilon | c****n@g****m | 1,614 |
| Jonas Kalderstam | j****s@k****e | 87 |
| Noah | n****h@v****m | 20 |
| Sean Reed | s****n@s****m | 12 |
| Ben Kuhn | b****n@g****m | 10 |
| Paul Zivich | 3****h | 10 |
| Mike Williamson | t****w@g****m | 8 |
| AbdealiJK | a****i@g****m | 7 |
| Andrew Gartland | a****d@g****m | 6 |
| Deepyaman Datta | d****a@u****u | 6 |
| Vincent M | m****t@y****r | 5 |
| Gabriel | g****g@g****m | 5 |
| Alex Parij | p****x@g****m | 5 |
| lgmoneda | l****a@g****m | 5 |
| Arturo Moncada-Torres | 3****s | 5 |
| Badr-MOUFAD | b****d@e****a | 4 |
| Daniel Wilson | h****l@g****m | 4 |
| Kyle | k****e@g****m | 4 |
| mathurinm | m****s@g****m | 4 |
| Jona | y****e@g****m | 3 |
| JoseLlanes | j****4@g****m | 3 |
| Karthikeyan Singaravelan | t****i@g****m | 3 |
| Miguel Sancho Peña | m****u@g****m | 3 |
| santon | s****n@i****m | 3 |
| Niels Bantilan | n****s@p****m | 3 |
| Harsh Gadgil | h****l@g****m | 3 |
| jlim13@cs.unc.edu | j****3@c****u | 2 |
| invictus2010 | j****n@g****m | 2 |
| davegolland | d****6@g****m | 2 |
| Younes | u****1@g****m | 2 |
| and 90 more... | ||
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 4 months ago
All Time
- Total issues: 176
- Total pull requests: 40
- Average time to close issues: 7 months
- Average time to close pull requests: 20 days
- Total issue authors: 141
- Total pull request authors: 29
- Average comments per issue: 2.62
- Average comments per pull request: 1.48
- Merged pull requests: 31
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 15
- Pull requests: 7
- Average time to close issues: about 12 hours
- Average time to close pull requests: 12 days
- Issue authors: 14
- Pull request authors: 6
- Average comments per issue: 1.0
- Average comments per pull request: 1.43
- Merged pull requests: 3
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- CamDavidsonPilon (14)
- SurajitTest (5)
- ibobak (4)
- daniyalshahzad (3)
- fkiraly (3)
- dpellow (2)
- NickCEBM (2)
- Zethson (2)
- kyleabeauchamp (2)
- dominicyu04 (2)
- benslack19 (2)
- RSHum23 (2)
- shilet (2)
- ayadasan (1)
- ensley (1)
Pull Request Authors
- CamDavidsonPilon (11)
- asarigun (2)
- FBruzzesi (2)
- mathematicalmichael (2)
- rvdinter (2)
- mathurinm (2)
- h-b-k-nishi (2)
- sbwiecko (2)
- Unessam (2)
- he7d3r (1)
- Kilo59 (1)
- Vincent-Maladiere (1)
- DanBasson (1)
- bofeng2018 (1)
- ewulczyn (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 5
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Total downloads:
- pypi 1,637,209 last-month
- Total docker downloads: 596,658
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Total dependent packages: 56
(may contain duplicates) -
Total dependent repositories: 515
(may contain duplicates) - Total versions: 464
- Total maintainers: 2
pypi.org: lifelines
Survival analysis in Python, including Kaplan Meier, Nelson Aalen and regression
- Homepage: https://github.com/CamDavidsonPilon/lifelines
- Documentation: https://lifelines.readthedocs.io/
- License: MIT
-
Latest release: 0.30.0
published about 1 year ago
Rankings
Maintainers (1)
proxy.golang.org: github.com/CamDavidsonPilon/lifelines
- Documentation: https://pkg.go.dev/github.com/CamDavidsonPilon/lifelines#section-documentation
- License: mit
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Latest release: v0.30.0
published about 1 year ago
Rankings
proxy.golang.org: github.com/camdavidsonpilon/lifelines
- Documentation: https://pkg.go.dev/github.com/camdavidsonpilon/lifelines#section-documentation
- License: mit
-
Latest release: v0.30.0
published about 1 year ago
Rankings
spack.io: py-lifelines
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.). *lifelines* is a pure Python implementation of the best parts of survival analysis.
- Homepage: https://github.com/CamDavidsonPilon/lifelines
- License: []
-
Latest release: 0.25.5
published over 3 years ago
Rankings
Maintainers (1)
conda-forge.org: lifelines
- Homepage: https://github.com/CamDavidsonPilon/lifelines
- License: MIT
-
Latest release: 0.27.4
published about 3 years ago
Rankings
Dependencies
- autograd >=1.3
- autograd-gamma >=0.3
- formulaic >=0.2.2
- matplotlib >=3.0
- numpy >=1.14.0
- pandas >=1.0.0
- scipy >=1.2.0
- black *
- check-wheel-contents *
- coverage >=4.4
- dill *
- flaky *
- mypy *
- pre-commit *
- prospector *
- pypandoc *
- pytest >=4.6
- pytest-cov *
- pytest-icdiff *
- scikit-learn >=0.22.0
- statsmodels *
- sybil *
- ipykernel *
- jupyter_client *
- nbconvert *
- nbsphinx *
- sphinx *
- sphinx_rtd_theme *
- dill *
- pytest-travis-fold *
- python-coveralls *
- seaborn *
- actions/checkout v2 composite
- actions/setup-python v2 composite
- actions/checkout v2 composite
- actions/setup-python v1 composite