How to Install and Uninstall python311-altair Package on openSuSE Tumbleweed
Last updated: November 14,2024
1. Install "python311-altair" package
This guide covers the steps necessary to install python311-altair on openSuSE Tumbleweed
$
sudo zypper refresh
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$
sudo zypper install
python311-altair
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2. Uninstall "python311-altair" package
Please follow the step by step instructions below to uninstall python311-altair on openSuSE Tumbleweed:
$
sudo zypper remove
python311-altair
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3. Information about the python311-altair package on openSuSE Tumbleweed
Information for package python311-altair:
-----------------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : python311-altair
Version : 5.2.0-1.1
Arch : noarch
Vendor : openSUSE
Installed Size : 13.4 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 : python311-altair
Version : 5.2.0-1.1
Arch : noarch
Vendor : openSUSE
Installed Size : 13.4 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.