How to Install and Uninstall python312-altair Package on openSuSE Tumbleweed
Last updated: December 29,2024
1. Install "python312-altair" package
Please follow the instructions below to install python312-altair on openSuSE Tumbleweed
$
sudo zypper refresh
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$
sudo zypper install
python312-altair
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2. Uninstall "python312-altair" package
This guide covers the steps necessary to uninstall python312-altair on openSuSE Tumbleweed:
$
sudo zypper remove
python312-altair
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3. Information about the python312-altair package on openSuSE Tumbleweed
Information for package python312-altair:
-----------------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : python312-altair
Version : 5.2.0-1.1
Arch : noarch
Vendor : openSUSE
Installed Size : 13.2 MiB
Installed : No
Status : not installed
Source package : python-altair-5.2.0-1.1.src
Upstream URL : https://github.com/altair-viz/altair
Summary : Declarative statistical visualization library for Python
Description :
This package provides a Python API for building statistical visualizations
in a declarative manner. This API contains no actual visualization rendering
code, but instead emits JSON data structures following the `Vega-Lite`_
specification. For convenience, Altair can optionally use `ipyvega`_ to
seamlessly display client-side renderings in the Jupyter notebook.
-----------------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : python312-altair
Version : 5.2.0-1.1
Arch : noarch
Vendor : openSUSE
Installed Size : 13.2 MiB
Installed : No
Status : not installed
Source package : python-altair-5.2.0-1.1.src
Upstream URL : https://github.com/altair-viz/altair
Summary : Declarative statistical visualization library for Python
Description :
This package provides a Python API for building statistical visualizations
in a declarative manner. This API contains no actual visualization rendering
code, but instead emits JSON data structures following the `Vega-Lite`_
specification. For convenience, Altair can optionally use `ipyvega`_ to
seamlessly display client-side renderings in the Jupyter notebook.