How to Install and Uninstall python39-statsmodels Package on openSuSE Tumbleweed
Last updated: November 23,2024
1. Install "python39-statsmodels" package
Please follow the guidance below to install python39-statsmodels on openSuSE Tumbleweed
$
sudo zypper refresh
Copied
$
sudo zypper install
python39-statsmodels
Copied
2. Uninstall "python39-statsmodels" package
This guide covers the steps necessary to uninstall python39-statsmodels on openSuSE Tumbleweed:
$
sudo zypper remove
python39-statsmodels
Copied
3. Information about the python39-statsmodels package on openSuSE Tumbleweed
Information for package python39-statsmodels:
---------------------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : python39-statsmodels
Version : 0.14.1-2.1
Arch : x86_64
Vendor : openSUSE
Installed Size : 46.4 MiB
Installed : No
Status : not installed
Source package : python-statsmodels-0.14.1-2.1.src
Upstream URL : https://github.com/statsmodels/statsmodels
Summary : A Python module that allows users to explore data
Description :
Statsmodels is a Python module that allows users to explore data,
estimate statistical models, and perform statistical tests.
An extensive list of descriptive statistics, statistical tests,
plotting functions, and result statistics are available for different
types of data and each estimator. Researchers across fields may find
that statsmodels fully meets their needs for statistical computing
and data analysis in Python.
---------------------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : python39-statsmodels
Version : 0.14.1-2.1
Arch : x86_64
Vendor : openSUSE
Installed Size : 46.4 MiB
Installed : No
Status : not installed
Source package : python-statsmodels-0.14.1-2.1.src
Upstream URL : https://github.com/statsmodels/statsmodels
Summary : A Python module that allows users to explore data
Description :
Statsmodels is a Python module that allows users to explore data,
estimate statistical models, and perform statistical tests.
An extensive list of descriptive statistics, statistical tests,
plotting functions, and result statistics are available for different
types of data and each estimator. Researchers across fields may find
that statsmodels fully meets their needs for statistical computing
and data analysis in Python.