Ubuntu
pandas package

pandas 0.23.3+dfsg-4ubuntu6 source package in Ubuntu

Changelog

pandas (0.23.3+dfsg-4ubuntu6) focal; urgency=medium

  * Backport some fixes for compatibility with numpy 1.17+.
  * Stop ignoring test results on Python 3.7.

 -- Michael Hudson-Doyle <email address hidden>  Wed, 06 Nov 2019 13:15:32 +1300

Upload details

Uploaded by:
Michael Hudson-Doyle
Uploaded to:
Focal
Original maintainer:
Ubuntu Developers
Architectures:
any all
Section:
python
Urgency:
Medium Urgency

See full publishing history Publishing

Series Pocket Published Component Section

Downloads

File Size SHA-256 Checksum
pandas_0.23.3+dfsg.orig.tar.gz 7.2 MiB 061409fc945cdeb85f366583e29eacee06c8c70b694ad6187d9b487a1133565c
pandas_0.23.3+dfsg-4ubuntu6.debian.tar.xz 3.5 MiB 71ace1f9457e1402a12a7c3b797ae086505d4a3f81ae4ed41fe80d96c33f8fe8
pandas_0.23.3+dfsg-4ubuntu6.dsc 3.3 KiB 288f7bc7d774804cd35c849f9b1ae77e392d31f067837b419bd843f443f4b997

View changes file

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