Ubuntu
pandas package

pandas 1.3.5+dfsg-3 source package in Ubuntu

Changelog

pandas (1.3.5+dfsg-3) unstable; urgency=medium

  * Tests: be compatible with new fsspec.  (Closes: #1006170)
  * Re-enable numba tests.
  * Fix pyversions call.
  * Enable Salsa CI.
  * Update Lintian overrides.

 -- Rebecca N. Palmer <email address hidden>  Mon, 21 Feb 2022 07:35:51 +0000

Upload details

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

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Series Pocket Published Component Section
Jammy release universe python

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File Size SHA-256 Checksum
pandas_1.3.5+dfsg-3.dsc 4.4 KiB a980a4cbb9bca150db328546d6bdaa05550f49b2262677094d49fbe20c4b002a
pandas_1.3.5+dfsg.orig.tar.xz 7.8 MiB f4e0716afbae3ec09e869d28fd4d8dfc05b1faaa8f7b545d24effd105ca0b3ea
pandas_1.3.5+dfsg-3.debian.tar.xz 64.8 KiB 9ec67144ef96572fddad39e36cf06cadeaae6b3008bfce7d0f7d6ecad4474668

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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