pandas 0.23.3+dfsg-4ubuntu4 source package in Ubuntu
Changelog
pandas (0.23.3+dfsg-4ubuntu4) focal; urgency=medium
* Ignore test results for Python 3.8 for now.
* Also ignore test results for Python 3.7 for now, introduced by
a new NumPy version.
-- Matthias Klose <email address hidden> Mon, 21 Oct 2019 18:28:36 +0200
Upload details
- Uploaded by:
- Matthias Klose
- 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-4ubuntu4.debian.tar.xz | 3.5 MiB | c3be2ceb658977f096b9bec9c771c1dcb5b4f587d7321420a7e39ed1f15ad86c |
| pandas_0.23.3+dfsg-4ubuntu4.dsc | 3.4 KiB | 23e3399e63a61d99f294a26ad8093842f65154bf35cba488805a464f6d7800c5 |
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
