How to Install and Uninstall python-pandas-doc Package on Ubuntu 21.10 (Impish Indri)

Last updated: May 14,2024

1. Install "python-pandas-doc" package

This guide let you learn how to install python-pandas-doc on Ubuntu 21.10 (Impish Indri)


    
        
            $
        

        
            
                sudo apt update
            
                    
    
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            $
        

        
            
                sudo apt install
            
                        
                python-pandas-doc
            
                    
    
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2. Uninstall "python-pandas-doc" package

Please follow the steps below to uninstall python-pandas-doc on Ubuntu 21.10 (Impish Indri):


    
        
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                sudo apt remove
            
                        
                python-pandas-doc
            
                    
    
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            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

3. Information about the python-pandas-doc package on Ubuntu 21.10 (Impish Indri)

Package: python-pandas-doc
Architecture: all
Version: 1.1.5+dfsg-2
Priority: optional
Section: universe/doc
Source: pandas
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Science Team
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 49017
Depends: libjs-sphinxdoc (>= 2.4.3-5~)
Suggests: python3-pandas
Filename: pool/universe/p/pandas/python-pandas-doc_1.1.5+dfsg-2_all.deb
Size: 8184904
MD5sum: 75a46f7d98f9cb59b2db3d54a74392f3
SHA1: 05b41abef07c7ffb96eb3b1eac95f1cbf6d2aabb
SHA256: 64d781fb37323cd39c44100bfa0ab071606dfffb76269f70c2141e3710362387
SHA512: a99058c6c6f64d0d6dd02fa93c27d023a76849539fb57653396066cfc71aa046fd1f38070edb2644e51e49f584c0bb76f9dac5cb4f3df7de5dd0c86a2b3f6ee2
Homepage: https://pandas.pydata.org/
Description-en: data structures for "relational" or "labeled" data - documentation
pandas is a Python package providing fast, flexible, and expressive
data structures designed to make working with "relational" or
"labeled" data both easy and intuitive. It aims to be the fundamental
high-level building block for doing practical, real world data
analysis in Python. pandas is well suited for many different kinds of
data:
.
- Tabular data with heterogeneously-typed columns, as in an SQL
table or Excel spreadsheet
- Ordered and unordered (not necessarily fixed-frequency) time
series data.
- Arbitrary matrix data (homogeneously typed or heterogeneous) with
row and column labels
- Any other form of observational / statistical data sets. The data
actually need not be labeled at all to be placed into a pandas
data structure
.
This package contains the documentation.
Description-md5: 7a749591db25bd458e01e853e9fcd291