How to Install and Uninstall python312-vega_datasets Package on openSuSE Tumbleweed
Last updated: November 08,2024
1. Install "python312-vega_datasets" package
This is a short guide on how to install python312-vega_datasets on openSuSE Tumbleweed
$
sudo zypper refresh
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$
sudo zypper install
python312-vega_datasets
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2. Uninstall "python312-vega_datasets" package
This is a short guide on how to uninstall python312-vega_datasets on openSuSE Tumbleweed:
$
sudo zypper remove
python312-vega_datasets
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3. Information about the python312-vega_datasets package on openSuSE Tumbleweed
Information for package python312-vega_datasets:
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Repository : openSUSE-Tumbleweed-Oss
Name : python312-vega_datasets
Version : 0.9.0-1.13
Arch : noarch
Vendor : openSUSE
Installed Size : 918.4 KiB
Installed : No
Status : not installed
Source package : python-vega_datasets-0.9.0-1.13.src
Upstream URL : http://github.com/altair-viz/vega_datasets
Summary : A Python package for offline access to Vega datasets
Description :
A Python package for offline access to vega datasets.
- Provide straightforward access in Python to the datasets made available
- return the results in the form of a Pandas dataframe
- wherever dataset size and/or license constraints make it possible, bundle the dataset with the package so that datasets can be loaded in the absence of a web connection
------------------------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : python312-vega_datasets
Version : 0.9.0-1.13
Arch : noarch
Vendor : openSUSE
Installed Size : 918.4 KiB
Installed : No
Status : not installed
Source package : python-vega_datasets-0.9.0-1.13.src
Upstream URL : http://github.com/altair-viz/vega_datasets
Summary : A Python package for offline access to Vega datasets
Description :
A Python package for offline access to vega datasets.
- Provide straightforward access in Python to the datasets made available
- return the results in the form of a Pandas dataframe
- wherever dataset size and/or license constraints make it possible, bundle the dataset with the package so that datasets can be loaded in the absence of a web connection