pandas 1.3.5+dfsg-2ubuntu1 source package in Ubuntu
Changelog
pandas (1.3.5+dfsg-2ubuntu1) jammy; urgency=medium
* d/p/fsspec-2022.01: fix tests to work with newer version of
python3-fsspec. Thanks to Thomas Li.
-- Robie Basak <email address hidden> Wed, 16 Feb 2022 02:34:58 +0000
Upload details
- Uploaded by:
- Robie Basak
- Uploaded to:
- Jammy
- 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_1.3.5+dfsg.orig.tar.xz | 7.8 MiB | f4e0716afbae3ec09e869d28fd4d8dfc05b1faaa8f7b545d24effd105ca0b3ea |
| pandas_1.3.5+dfsg-2ubuntu1.debian.tar.xz | 64.5 KiB | c10e000a2ee0db3ecea56e45926a7fd4383c04bfc6ec5aad3b5b267342d84ccf |
| pandas_1.3.5+dfsg-2ubuntu1.dsc | 4.4 KiB | c8470eb28ca5f51291e4220c73034a6cdbba41984991a90789de97e4efa7965c |
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
