Ubuntu
pandas package

pandas 1.5.3+dfsg-6ubuntu1 source package in Ubuntu

Changelog

pandas (1.5.3+dfsg-6ubuntu1) noble; urgency=medium

  * Cherry-pick partial upstream commit for Python 3.12 compatibility
  * Ignore remaining test failures for first build with Python 3.12

 -- Graham Inggs <email address hidden>  Thu, 16 Nov 2023 11:01:30 +0000

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Uploaded by:
Graham Inggs
Uploaded to:
Noble
Original maintainer:
Ubuntu Developers
Architectures:
any all
Section:
python
Urgency:
Medium Urgency

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File Size SHA-256 Checksum
pandas_1.5.3+dfsg.orig.tar.xz 8.6 MiB 5c50f7c36d93ed1e6e41fdd6c1116def08dadbe64245365e3410009bcbb557f3
pandas_1.5.3+dfsg-6ubuntu1.debian.tar.xz 70.8 KiB 9ec79771c97d74a857edbcc0a55ea696564f213ca8f0899f1ac9872365ed1cc3
pandas_1.5.3+dfsg-6ubuntu1.dsc 4.8 KiB 318e54baae1a5b40caeb0b3317b23834d2728afaf10652a4d7e74aa720304571

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Binary packages built by this source

python-pandas-doc: 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.

python3-pandas: 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.

python3-pandas-lib: low-level implementations and bindings for pandas

 This is a low-level package for python3-pandas providing
 architecture-dependent extensions.
 .
 Users should not need to install it directly.

python3-pandas-lib-dbgsym: debug symbols for python3-pandas-lib