pandas 0.25.3+dfsg-7 source package in Ubuntu
Changelog
pandas (0.25.3+dfsg-7) unstable; urgency=medium * Fix another test failure due to our warnings. * Skip rather than xfail crashing tests. -- Rebecca N. Palmer <email address hidden> Wed, 26 Feb 2020 18:45:58 +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 | |
---|---|---|---|---|
Focal | release | universe | python |
Downloads
File | Size | SHA-256 Checksum |
---|---|---|
pandas_0.25.3+dfsg-7.dsc | 3.9 KiB | 90ba731bdeb5d227ea34686434ae18205bdd53c42653cd54eb6bff8f8182fb80 |
pandas_0.25.3+dfsg.orig.tar.gz | 7.2 MiB | e6915f69b2536a32138207aae2e0e9188ba6048d6af81d24c4905cc58112eb1f |
pandas_0.25.3+dfsg-7.debian.tar.xz | 65.9 KiB | 68b4373d34ab3bf6fc8d9445b3d4135184b66ca3079b2b7bf4bfea3a1bfb2825 |
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: No summary available for python3-pandas-lib-dbgsym in ubuntu groovy.
No description available for python3-
pandas- lib-dbgsym in ubuntu groovy.