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 | 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 |
Available diffs
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