How to Install and Uninstall python3-dask-dataframe Package on openSUSE Leap

Last updated: May 14,2024

1. Install "python3-dask-dataframe" package

Here is a brief guide to show you how to install python3-dask-dataframe on openSUSE Leap


    
        
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                sudo zypper refresh
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo zypper install
            
                        
                python3-dask-dataframe
            
                    
    
    Copied

2. Uninstall "python3-dask-dataframe" package

This is a short guide on how to uninstall python3-dask-dataframe on openSUSE Leap:


    
        
            $
        

        
            
                sudo zypper remove
            
                        
                python3-dask-dataframe
            
                    
    
    Copied

3. Information about the python3-dask-dataframe package on openSUSE Leap

Information for package python3-dask-dataframe:
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Repository : Main Repository
Name : python3-dask-dataframe
Version : 1.1.1-bp155.2.16
Arch : noarch
Vendor : openSUSE
Installed Size : 2.8 MiB
Installed : No
Status : not installed
Source package : python-dask-1.1.1-bp155.2.16.src
Upstream URL : http://github.com/ContinuumIO/dask/
Summary : Pandas-like DataFrame data structure for dask
Description :
A minimal task scheduling abstraction and parallel arrays.
* dask is a specification to describe task dependency graphs.
* dask.array is a drop-in NumPy replacement (for a subset of NumPy) that
encodes blocked algorithms in dask dependency graphs.
* dask.async is a shared-memory asynchronous scheduler that efficiently
executes dask dependency graphs on multiple cores.
This package contains the dask DataFrame class.
A Dask DataFrame is a large parallel dataframe composed of many
smaller Pandas dataframes, split along the index. These pandas
dataframes may live on disk for larger-than-memory computing
on a single machine, or on many different machines in a cluster.