Ubuntu
pandas package

pandas 1.5.3+dfsg-5 source package in Ubuntu

Changelog

pandas (1.5.3+dfsg-5) unstable; urgency=medium

  * Backport the following from experimental:
    - Don't use numexpr for **, as it has different overflow behaviour.
    - Tests: don't use : in numexpr variable names.
    - Use tzdata-legacy where old-style timezone names are used.
    - Clean up after tests.
    - Tests: re-enable numba tests.

 -- Rebecca N. Palmer <email address hidden>  Thu, 17 Aug 2023 20:11:19 +0100

Upload details

Uploaded by:
Debian Science Team
Uploaded to:
Sid
Original maintainer:
Debian Science Team
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_1.5.3+dfsg-5.dsc 4.8 KiB fa03187a2dd13fd5af81ec336920e030177af8465ab85da3cd266654e0996b95
pandas_1.5.3+dfsg.orig.tar.xz 8.6 MiB 5c50f7c36d93ed1e6e41fdd6c1116def08dadbe64245365e3410009bcbb557f3
pandas_1.5.3+dfsg-5.debian.tar.xz 70.5 KiB e65fb9eac749dadfab12ddd8a2166ef9555bc546cc503b6c4f4c4e4c930e2a0a

Available diffs

No changes file available.

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