Ubuntu
pandas package

pandas 1.1.5+dfsg-2ubuntu1 source package in Ubuntu

Changelog

pandas (1.1.5+dfsg-2ubuntu1) jammy; urgency=medium

  * Disable tests for first build with python3.10

 -- Graham Inggs <email address hidden>  Tue, 02 Nov 2021 06:37:51 +0000

Upload details

Uploaded by:
Graham Inggs
Uploaded to:
Jammy
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_1.1.5+dfsg.orig.tar.xz 5.9 MiB 24ec7bbf24aaf7504c829bec2bfa2cc9df3d307c7dce9f84f7f41693bccf6e55
pandas_1.1.5+dfsg-2ubuntu1.debian.tar.xz 63.0 KiB be69567eb8190d4e1342b611a3b35bb47c928528aca3456e33acd620b3efccfe
pandas_1.1.5+dfsg-2ubuntu1.dsc 4.4 KiB 38d3a28824cf99551ea509397339ebd9d4542cab018dc4ed6b8628f02962a651

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