%global _empty_manifest_terminate_build 0 Name: python-lifelines Version: 0.27.4 Release: 1 Summary: Survival analysis in Python, including Kaplan Meier, Nelson Aalen and regression License: MIT URL: https://github.com/CamDavidsonPilon/lifelines Source0: https://mirrors.nju.edu.cn/pypi/web/packages/c8/c4/0b6a0d2d72a26a65e14a088e8f5f35efcbcf0589310b75f5abd63b7c0a97/lifelines-0.27.4.tar.gz BuildArch: noarch Requires: python3-numpy Requires: python3-scipy Requires: python3-pandas Requires: python3-matplotlib Requires: python3-autograd Requires: python3-autograd-gamma Requires: python3-formulaic %description ![](http://i.imgur.com/EOowdSD.png) [![PyPI version](https://badge.fury.io/py/lifelines.svg)](https://badge.fury.io/py/lifelines) [![Anaconda-Server Badge](https://anaconda.org/conda-forge/lifelines/badges/version.svg )](https://conda.anaconda.org/conda-forge) [![DOI](https://zenodo.org/badge/12420595.svg)](https://zenodo.org/badge/latestdoi/12420595) [What is survival analysis and why should I learn it?](http://lifelines.readthedocs.org/en/latest/Survival%20Analysis%20intro.html) 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](http://lifelines.readthedocs.org/en/latest/index.html) ## Contact - Start a conversation in our [Discussions room](https://github.com/CamDavidsonPilon/lifelines/discussions). - Some users have posted common questions at [stats.stackexchange.com](https://stats.stackexchange.com/search?tab=votes&q=%22lifelines%22%20is%3aquestion) - creating an issue in the [Github repository](https://github.com/camdavidsonpilon/lifelines). ## Development See our [Contributing](https://github.com/CamDavidsonPilon/lifelines/blob/master/.github/CONTRIBUTING.md) guidelines. %package -n python3-lifelines Summary: Survival analysis in Python, including Kaplan Meier, Nelson Aalen and regression Provides: python-lifelines BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-lifelines ![](http://i.imgur.com/EOowdSD.png) [![PyPI version](https://badge.fury.io/py/lifelines.svg)](https://badge.fury.io/py/lifelines) [![Anaconda-Server Badge](https://anaconda.org/conda-forge/lifelines/badges/version.svg )](https://conda.anaconda.org/conda-forge) [![DOI](https://zenodo.org/badge/12420595.svg)](https://zenodo.org/badge/latestdoi/12420595) [What is survival analysis and why should I learn it?](http://lifelines.readthedocs.org/en/latest/Survival%20Analysis%20intro.html) 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](http://lifelines.readthedocs.org/en/latest/index.html) ## Contact - Start a conversation in our [Discussions room](https://github.com/CamDavidsonPilon/lifelines/discussions). - Some users have posted common questions at [stats.stackexchange.com](https://stats.stackexchange.com/search?tab=votes&q=%22lifelines%22%20is%3aquestion) - creating an issue in the [Github repository](https://github.com/camdavidsonpilon/lifelines). ## Development See our [Contributing](https://github.com/CamDavidsonPilon/lifelines/blob/master/.github/CONTRIBUTING.md) guidelines. %package help Summary: Development documents and examples for lifelines Provides: python3-lifelines-doc %description help ![](http://i.imgur.com/EOowdSD.png) [![PyPI version](https://badge.fury.io/py/lifelines.svg)](https://badge.fury.io/py/lifelines) [![Anaconda-Server Badge](https://anaconda.org/conda-forge/lifelines/badges/version.svg )](https://conda.anaconda.org/conda-forge) [![DOI](https://zenodo.org/badge/12420595.svg)](https://zenodo.org/badge/latestdoi/12420595) [What is survival analysis and why should I learn it?](http://lifelines.readthedocs.org/en/latest/Survival%20Analysis%20intro.html) 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](http://lifelines.readthedocs.org/en/latest/index.html) ## Contact - Start a conversation in our [Discussions room](https://github.com/CamDavidsonPilon/lifelines/discussions). - Some users have posted common questions at [stats.stackexchange.com](https://stats.stackexchange.com/search?tab=votes&q=%22lifelines%22%20is%3aquestion) - creating an issue in the [Github repository](https://github.com/camdavidsonpilon/lifelines). ## Development See our [Contributing](https://github.com/CamDavidsonPilon/lifelines/blob/master/.github/CONTRIBUTING.md) guidelines. %prep %autosetup -n lifelines-0.27.4 %build %py3_build %install %py3_install install -d -m755 %{buildroot}/%{_pkgdocdir} if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi pushd %{buildroot} if [ -d usr/lib ]; then find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst fi if [ -d usr/lib64 ]; then find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst fi if [ -d usr/bin ]; then find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst fi if [ -d usr/sbin ]; then find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst fi touch doclist.lst if [ -d usr/share/man ]; then find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst fi popd mv %{buildroot}/filelist.lst . mv %{buildroot}/doclist.lst . %files -n python3-lifelines -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Fri Apr 21 2023 Python_Bot - 0.27.4-1 - Package Spec generated