Ubuntu
pandas package

pandas 1.3.5+dfsg-2 source package in Ubuntu

Changelog

pandas (1.3.5+dfsg-2) unstable; urgency=medium

  * Temporarily skip numba tests (see LP#1951814).

 -- Rebecca N. Palmer <email address hidden>  Fri, 28 Jan 2022 19:22:53 +0000

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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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File Size SHA-256 Checksum
pandas_1.3.5+dfsg-2.dsc 4.3 KiB c796fa028a33331843399f6132ea00017fbc50954f8beb9b5fa8b7b53d963567
pandas_1.3.5+dfsg.orig.tar.xz 7.8 MiB f4e0716afbae3ec09e869d28fd4d8dfc05b1faaa8f7b545d24effd105ca0b3ea
pandas_1.3.5+dfsg-2.debian.tar.xz 64.1 KiB 837bfaa9fffeb5864be24014f3aaab3ef34db31f5600252d9c7db5c8fed346ca

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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