Ubuntu
pandas package

pandas 1.5.2+dfsg-6 source package in Ubuntu

Changelog

pandas (1.5.2+dfsg-6) unstable; urgency=medium

  * Move xarray to Build-Depends-Indep to break circular dependency.

 -- Rebecca N. Palmer <email address hidden>  Wed, 11 Jan 2023 07:34:28 +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_1.5.2+dfsg-6.dsc 4.6 KiB f6546177a7194255f67888fe450a71854a56a2aaed0586fa4e1c2c88d2c19f48
pandas_1.5.2+dfsg.orig.tar.xz 8.6 MiB ca4360f3af437ac94d0cbaa58202a6bba5621916e3e61c6cd858b81b2d429686
pandas_1.5.2+dfsg-6.debian.tar.xz 69.7 KiB 67846e9e35dd8923b5e7686537d1deb7e6af912194b8482a90a9defd2a218059

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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