pandas 2.1.4+dfsg-4ubuntu2 source package in Ubuntu
Changelog
pandas (2.1.4+dfsg-4ubuntu2) noble; urgency=medium
* Revert changes from 2.1.4+dfsg-4ubuntu1
* Move Build-Depends: python3-tables to Build-Depends-Indep,
as it is not available on all architectures
-- Graham Inggs <email address hidden> Mon, 12 Feb 2024 20:10:03 +0000
Upload details
- Uploaded by:
- Graham Inggs
- Uploaded to:
- Noble
- 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_2.1.4+dfsg.orig.tar.xz | 10.6 MiB | b516a6f52b8be6ae5461666143f0c9f9013761c26cc6109ffc7253e0b3119502 |
| pandas_2.1.4+dfsg-4ubuntu2.debian.tar.xz | 76.1 KiB | 3a6e7b4beea3ef63e1ee2e833f223b207543991b8089d0082a4663e2565c9260 |
| pandas_2.1.4+dfsg-4ubuntu2.dsc | 5.0 KiB | 56a8fc8bf1e2e62d61cf9d10857418adf793d586c45586a2550b5d4a664f265e |
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
