How to Install and Uninstall python3-pandas Package on Kali Linux
Last updated: November 06,2024
1. Install "python3-pandas" package
Please follow the instructions below to install python3-pandas on Kali Linux
$
sudo apt update
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$
sudo apt install
python3-pandas
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2. Uninstall "python3-pandas" package
Please follow the step by step instructions below to uninstall python3-pandas on Kali Linux:
$
sudo apt remove
python3-pandas
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$
sudo apt autoclean && sudo apt autoremove
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3. Information about the python3-pandas package on Kali Linux
Package: python3-pandas
Source: pandas
Version: 2.1.4+dfsg-5
Installed-Size: 21513
Maintainer: Debian Science Team
Architecture: all
Depends: python3-dateutil, python3-numpy, python3-numpy (>= 1:1.23.2~) | python3-supported-max (<< 3.11) | python3-supported-min (>= 3.12), python3-numpy (>= 1:1.23.2~) | python3-supported-max (<< 3.12), python3-numpy (>= 1:1.23.2~) | python3-supported-min (>= 3.11), python3-tz (>= 2022.1~), python3:any, python3-pandas-lib (>= 2.1.4+dfsg), python3-pkg-resources, tzdata
Recommends: python3-scipy, python3-matplotlib, python3-bottleneck, python3-numexpr, python3-odf, python3-openpyxl, python3-bs4, python3-html5lib, python3-lxml, python3-tables, python3-jinja2
Suggests: python-pandas-doc, python3-statsmodels
Breaks: augur (<= 24.0.0-1), cnvkit (<< 0.9.10~), python3-altair (<< 5.0.1~), python3-anndata (<= 0.8.0-4), python3-biom-format (<< 2.1.15.2-3~), python3-cfgrib (<= 0.9.9-1), python3-cooler (<< 0.9.3~), python3-dask (<< 2023.12.1~), python3-dials (<< 3.17.0~), python3-dyda (<= 1.41.1-1.1), python3-emperor (<< 1.0.3+ds-9~), python3-esda (<= 2.5.1-1), python3-feather-format (<< 0.3.1+dfsg1-8~), python3-hypothesis (<< 6.83.1~), python3-joypy (<= 0.2.2-2), python3-jsonpickle (<< 3.0.2+dfsg-1~), python3-mirtop (<< 0.4.25-5~), python3-nanoget (<< 1.19.3~), python3-pauvre (<< 0.2.3-3~), python3-pyani (<< 0.2.12-3~), python3-pymatgen (<< 2024.1.27~), python3-pyranges (<= 0.0.111+ds-6), python3-seaborn (<< 0.13.0~), python3-skbio (<< 0.5.9~), python3-sklearn-pandas (<= 2.2.0-1.1), python3-statsmodels (<< 0.13.5~), python3-sunpy (<< 5.1.0-1~), python3-ulmo (<= 0.8.8+dfsg1-2), python3-upsetplot (<< 0.8.0-3~), python3-xarray-sentinel (<< 0.9.5+ds-2~), q2-cutadapt (<< 2023.7.0-1~), q2-demux (<= 2023.9.1+dfsg-1), q2-quality-control (<= 2022.11.1-2), q2-taxa (<= 2023.9.0+dfsg-1), q2-types (<= 2023.9.0-1), q2templates (<= 2023.9.0+ds-1)
Size: 3015072
SHA256: 0e64aaceba48c0a20023250262c9e519a2d3962b09ec654edfa04f954743ec18
SHA1: a7ad0e832a243cb61b9afc3e17d3cc76329a9b75
MD5sum: 4b2628a9497bddc8123eee879e4d06b4
Description: data structures for "relational" or "labeled" data
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 Python 3 version.
Description-md5:
Homepage: https://pandas.pydata.org/
Tag: devel::lang:python, devel::library, field::mathematics,
field::statistics, implemented-in::python, role::devel-lib
Section: python
Priority: optional
Filename: pool/main/p/pandas/python3-pandas_2.1.4+dfsg-5_all.deb
Source: pandas
Version: 2.1.4+dfsg-5
Installed-Size: 21513
Maintainer: Debian Science Team
Architecture: all
Depends: python3-dateutil, python3-numpy, python3-numpy (>= 1:1.23.2~) | python3-supported-max (<< 3.11) | python3-supported-min (>= 3.12), python3-numpy (>= 1:1.23.2~) | python3-supported-max (<< 3.12), python3-numpy (>= 1:1.23.2~) | python3-supported-min (>= 3.11), python3-tz (>= 2022.1~), python3:any, python3-pandas-lib (>= 2.1.4+dfsg), python3-pkg-resources, tzdata
Recommends: python3-scipy, python3-matplotlib, python3-bottleneck, python3-numexpr, python3-odf, python3-openpyxl, python3-bs4, python3-html5lib, python3-lxml, python3-tables, python3-jinja2
Suggests: python-pandas-doc, python3-statsmodels
Breaks: augur (<= 24.0.0-1), cnvkit (<< 0.9.10~), python3-altair (<< 5.0.1~), python3-anndata (<= 0.8.0-4), python3-biom-format (<< 2.1.15.2-3~), python3-cfgrib (<= 0.9.9-1), python3-cooler (<< 0.9.3~), python3-dask (<< 2023.12.1~), python3-dials (<< 3.17.0~), python3-dyda (<= 1.41.1-1.1), python3-emperor (<< 1.0.3+ds-9~), python3-esda (<= 2.5.1-1), python3-feather-format (<< 0.3.1+dfsg1-8~), python3-hypothesis (<< 6.83.1~), python3-joypy (<= 0.2.2-2), python3-jsonpickle (<< 3.0.2+dfsg-1~), python3-mirtop (<< 0.4.25-5~), python3-nanoget (<< 1.19.3~), python3-pauvre (<< 0.2.3-3~), python3-pyani (<< 0.2.12-3~), python3-pymatgen (<< 2024.1.27~), python3-pyranges (<= 0.0.111+ds-6), python3-seaborn (<< 0.13.0~), python3-skbio (<< 0.5.9~), python3-sklearn-pandas (<= 2.2.0-1.1), python3-statsmodels (<< 0.13.5~), python3-sunpy (<< 5.1.0-1~), python3-ulmo (<= 0.8.8+dfsg1-2), python3-upsetplot (<< 0.8.0-3~), python3-xarray-sentinel (<< 0.9.5+ds-2~), q2-cutadapt (<< 2023.7.0-1~), q2-demux (<= 2023.9.1+dfsg-1), q2-quality-control (<= 2022.11.1-2), q2-taxa (<= 2023.9.0+dfsg-1), q2-types (<= 2023.9.0-1), q2templates (<= 2023.9.0+ds-1)
Size: 3015072
SHA256: 0e64aaceba48c0a20023250262c9e519a2d3962b09ec654edfa04f954743ec18
SHA1: a7ad0e832a243cb61b9afc3e17d3cc76329a9b75
MD5sum: 4b2628a9497bddc8123eee879e4d06b4
Description: data structures for "relational" or "labeled" data
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 Python 3 version.
Description-md5:
Homepage: https://pandas.pydata.org/
Tag: devel::lang:python, devel::library, field::mathematics,
field::statistics, implemented-in::python, role::devel-lib
Section: python
Priority: optional
Filename: pool/main/p/pandas/python3-pandas_2.1.4+dfsg-5_all.deb