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|
%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
[](https://badge.fury.io/py/lifelines)
[](https://conda.anaconda.org/conda-forge)
[](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
[](https://badge.fury.io/py/lifelines)
[](https://conda.anaconda.org/conda-forge)
[](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
[](https://badge.fury.io/py/lifelines)
[](https://conda.anaconda.org/conda-forge)
[](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
* Mon Apr 10 2023 Python_Bot <Python_Bot@openeuler.org> - 0.27.4-1
- Package Spec generated
|
