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%global _empty_manifest_terminate_build 0
Name: python-weightedstats
Version: 0.4.1
Release: 1
Summary: Mean, weighted mean, median, weighted median
License: MIT
URL: https://github.com/tinybike/weightedstats
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/da/a5/f5c0e601a610e4618316be3155febbbec98994788fcc0e9d8080369266ec/weightedstats-0.4.1.tar.gz
BuildArch: noarch
%description
Python functions to calculate the mean, weighted mean, median, and weighted median.
Installation
^^^^^^^^^^^^
The easiest way to install WeightedStats is to use pip::
$ pip install weightedstats
Usage
^^^^^
WeightedStats includes four functions (mean, weighted_mean, median, weighted_median) which accept lists as arguments, and two functions (numpy_weighted_mean, numpy weighted_median) which accept either lists or numpy arrays.
Example:
import weightedstats as ws
my_data = [1, 2, 3, 4, 5]
my_weights = [10, 1, 1, 1, 9]
# Ordinary (unweighted) mean and median
ws.mean(my_data) # equivalent to ws.weighted_mean(my_data)
ws.median(my_data) # equivalent to ws.weighted_median(my_data)
# Weighted mean and median
ws.weighted_mean(my_data, weights=my_weights)
ws.weighted_median(my_data, weights=my_weights)
# Special weighted mean and median functions for use with numpy arrays
ws.numpy_weighted_mean(my_data, weights=my_weights)
ws.numpy_weighted_median(my_data, weights=my_weights)
Tests
^^^^^
Unit tests are in the test/ directory.
%package -n python3-weightedstats
Summary: Mean, weighted mean, median, weighted median
Provides: python-weightedstats
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-weightedstats
Python functions to calculate the mean, weighted mean, median, and weighted median.
Installation
^^^^^^^^^^^^
The easiest way to install WeightedStats is to use pip::
$ pip install weightedstats
Usage
^^^^^
WeightedStats includes four functions (mean, weighted_mean, median, weighted_median) which accept lists as arguments, and two functions (numpy_weighted_mean, numpy weighted_median) which accept either lists or numpy arrays.
Example:
import weightedstats as ws
my_data = [1, 2, 3, 4, 5]
my_weights = [10, 1, 1, 1, 9]
# Ordinary (unweighted) mean and median
ws.mean(my_data) # equivalent to ws.weighted_mean(my_data)
ws.median(my_data) # equivalent to ws.weighted_median(my_data)
# Weighted mean and median
ws.weighted_mean(my_data, weights=my_weights)
ws.weighted_median(my_data, weights=my_weights)
# Special weighted mean and median functions for use with numpy arrays
ws.numpy_weighted_mean(my_data, weights=my_weights)
ws.numpy_weighted_median(my_data, weights=my_weights)
Tests
^^^^^
Unit tests are in the test/ directory.
%package help
Summary: Development documents and examples for weightedstats
Provides: python3-weightedstats-doc
%description help
Python functions to calculate the mean, weighted mean, median, and weighted median.
Installation
^^^^^^^^^^^^
The easiest way to install WeightedStats is to use pip::
$ pip install weightedstats
Usage
^^^^^
WeightedStats includes four functions (mean, weighted_mean, median, weighted_median) which accept lists as arguments, and two functions (numpy_weighted_mean, numpy weighted_median) which accept either lists or numpy arrays.
Example:
import weightedstats as ws
my_data = [1, 2, 3, 4, 5]
my_weights = [10, 1, 1, 1, 9]
# Ordinary (unweighted) mean and median
ws.mean(my_data) # equivalent to ws.weighted_mean(my_data)
ws.median(my_data) # equivalent to ws.weighted_median(my_data)
# Weighted mean and median
ws.weighted_mean(my_data, weights=my_weights)
ws.weighted_median(my_data, weights=my_weights)
# Special weighted mean and median functions for use with numpy arrays
ws.numpy_weighted_mean(my_data, weights=my_weights)
ws.numpy_weighted_median(my_data, weights=my_weights)
Tests
^^^^^
Unit tests are in the test/ directory.
%prep
%autosetup -n weightedstats-0.4.1
%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-weightedstats -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Wed May 10 2023 Python_Bot <Python_Bot@openeuler.org> - 0.4.1-1
- Package Spec generated
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