Ubuntu
pandas package

pandas 0.25.3+dfsg-5 source package in Ubuntu

Changelog

pandas (0.25.3+dfsg-5) unstable; urgency=medium

  * Backport packaging from experimental:
    - Remove unnecessary test skips, and reorganize remaining ones.
    - Use xfails instead of skips.
    - Add warnings for the known non-x86 breakages
      (NaN -> datetime #877754, HDF and Stata I/O #877419).
    - Tell I/O tests where to find the source tree's test data
      instead of skipping them.
    - Stop using deprecated envvar/tag names.
    - Use https for links where available.

 -- Rebecca N. Palmer <email address hidden>  Mon, 24 Feb 2020 22:38:26 +0000

Upload details

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_0.25.3+dfsg-5.dsc 3.8 KiB c9695d72d4f77341db03c6db324ea7401c5df2a49b95d5dc8b1e7c680738d47a
pandas_0.25.3+dfsg.orig.tar.gz 7.2 MiB e6915f69b2536a32138207aae2e0e9188ba6048d6af81d24c4905cc58112eb1f
pandas_0.25.3+dfsg-5.debian.tar.xz 64.4 KiB ea34b0bebf3cc590fc4eb27a5bfcdbf2d1ae5dd637dcb38df090af62a858757c

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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