pandas 0.25.3+dfsg-6 source package in Ubuntu
Changelog
pandas (0.25.3+dfsg-6) unstable; urgency=medium * Don't fail tests on our own warnings. * Xfail some more HDF tests on non-x86 architectures. * Warn that clipboard I/O is broken on big-endian architectures and xfail test. * Use pytest-forked to isolate (already xfailed) crashing test. * Xfail tests that use no-longer-existing URLs. -- Rebecca N. Palmer <email address hidden> Wed, 26 Feb 2020 07:40:25 +0000
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 | Published | Component | Section |
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Downloads
File | Size | SHA-256 Checksum |
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pandas_0.25.3+dfsg-6.dsc | 3.9 KiB | 679d41a78dd7b1a34ac39a75e6514e4adf43fb4feb84116fc95bd77adfca7631 |
pandas_0.25.3+dfsg.orig.tar.gz | 7.2 MiB | e6915f69b2536a32138207aae2e0e9188ba6048d6af81d24c4905cc58112eb1f |
pandas_0.25.3+dfsg-6.debian.tar.xz | 65.8 KiB | 3cd8083c2e07ce8e07b73a2c30cc1be96319364c5440bf84475a8abf14beb47e |
Available diffs
- diff from 0.25.3+dfsg-5 to 0.25.3+dfsg-6 (4.3 KiB)
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