How to Install and Uninstall perl-Statistics-Descriptive.noarch Package on Fedora 39
Last updated: May 20,2024
1. Install "perl-Statistics-Descriptive.noarch" package
This guide let you learn how to install perl-Statistics-Descriptive.noarch on Fedora 39
$
sudo dnf update
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$
sudo dnf install
perl-Statistics-Descriptive.noarch
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2. Uninstall "perl-Statistics-Descriptive.noarch" package
This is a short guide on how to uninstall perl-Statistics-Descriptive.noarch on Fedora 39:
$
sudo dnf remove
perl-Statistics-Descriptive.noarch
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$
sudo dnf autoremove
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3. Information about the perl-Statistics-Descriptive.noarch package on Fedora 39
Last metadata expiration check: 3:01:27 ago on Thu Mar 7 11:44:58 2024.
Available Packages
Name : perl-Statistics-Descriptive
Version : 3.0801
Release : 2.fc39
Architecture : noarch
Size : 72 k
Source : perl-Statistics-Descriptive-3.0801-2.fc39.src.rpm
Repository : fedora
Summary : Perl module of basic descriptive statistical functions
URL : https://metacpan.org/release/Statistics-Descriptive
License : ( GPL-1.0-or-later OR Artistic-1.0-Perl ) AND MIT
Description : This module provides basic functions used in descriptive statistics. It has
: an object oriented design and supports two different types of data storage
: and calculation objects: sparse and full. With the sparse method, none of
: the data is stored and only a few statistical measures are available. Using
: the full method, the entire data set is retained and additional functions
: are available.
Available Packages
Name : perl-Statistics-Descriptive
Version : 3.0801
Release : 2.fc39
Architecture : noarch
Size : 72 k
Source : perl-Statistics-Descriptive-3.0801-2.fc39.src.rpm
Repository : fedora
Summary : Perl module of basic descriptive statistical functions
URL : https://metacpan.org/release/Statistics-Descriptive
License : ( GPL-1.0-or-later OR Artistic-1.0-Perl ) AND MIT
Description : This module provides basic functions used in descriptive statistics. It has
: an object oriented design and supports two different types of data storage
: and calculation objects: sparse and full. With the sparse method, none of
: the data is stored and only a few statistical measures are available. Using
: the full method, the entire data set is retained and additional functions
: are available.