How to Install and Uninstall plfit-doc Package on Linux Mint 21 (Vanessa)

Last updated: November 26,2024

1. Install "plfit-doc" package

This guide let you learn how to install plfit-doc on Linux Mint 21 (Vanessa)


    
        
            $
        

        
            
                sudo apt update
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt install
            
                        
                plfit-doc
            
                    
    
    Copied

2. Uninstall "plfit-doc" package

This is a short guide on how to uninstall plfit-doc on Linux Mint 21 (Vanessa):


    
        
            $
        

        
            
                sudo apt remove
            
                        
                plfit-doc
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

3. Information about the plfit-doc package on Linux Mint 21 (Vanessa)

Package: plfit-doc
Architecture: all
Version: 0.9.3+ds-1ubuntu1
Multi-Arch: foreign
Priority: optional
Section: universe/doc
Source: plfit
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Science Maintainers
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 511
Enhances: libplfit-dev (= 0.9.3+ds-1ubuntu1), plfit (= 0.9.3+ds-1ubuntu1), python3-plfit (= 0.9.3+ds-1ubuntu1)
Filename: pool/universe/p/plfit/plfit-doc_0.9.3+ds-1ubuntu1_all.deb
Size: 95742
MD5sum: a66185992497aa585f7590351cabd748
SHA1: 259995bdeb0e47a1c5056df86e25199fdb0ce9d8
SHA256: f6d7ff4fbbe1a51d6fba2934cac2efe90783087a4ae34ea348e17438edbdb31a
SHA512: ef11088c098f7aead874607845864bfa33870b98942dac21b66c08e15e7087d63c3ea54fe9934d6b1febf7cb1e0146526469199edb807684bcfca53a15646dcb
Homepage: https://github.com/ntamas/plfit
Description: fitting power-law distributions to empirical data -- doc
Description-md5: 0b4c7e29b5902a37f1b29938923892e4