Ubuntu
pandas package

pandas 2.1.4+dfsg-3 source package in Ubuntu

Changelog

pandas (2.1.4+dfsg-3) unstable; urgency=medium

  * Add more transition Breaks (see #1043240).
  * Upload to unstable. (Closes: #1056828)
  * Tests: don't fail when (random) sum test input sums to near-0,
    use our paths, depend on pytest-localserver, skip broken test.
  * Docs: re-enable style.ipynb.

 -- Rebecca N. Palmer <email address hidden>  Thu, 01 Feb 2024 07:52:49 +0000

Upload details

Uploaded by:
Debian Science Team
Uploaded to:
Sid
Original maintainer:
Debian Science Team
Architectures:
any all
Section:
python
Urgency:
Medium Urgency

See full publishing history Publishing

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Downloads

File Size SHA-256 Checksum
pandas_2.1.4+dfsg-3.dsc 5.0 KiB 6a99b306160f072cb496013d42c4cddd8a86e4259a011d5f9ce44b24ac404a99
pandas_2.1.4+dfsg.orig.tar.xz 10.6 MiB b516a6f52b8be6ae5461666143f0c9f9013761c26cc6109ffc7253e0b3119502
pandas_2.1.4+dfsg-3.debian.tar.xz 75.8 KiB be5272b7c552364c87fe99e937756a0f313d6fdaaf3abbe87b3a7e56cb56b0c0

Available diffs

No changes file available.

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