pandas 2.1.4+dfsg-8 source package in Ubuntu
Changelog
pandas (2.1.4+dfsg-8) unstable; urgency=medium * Re-enable the documentation. * Bump Standards-Version to 4.7.0 (no changes needed). -- Rebecca N. Palmer <email address hidden> Sun, 21 Apr 2024 13:50:13 +0100
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 |
---|---|---|
pandas_2.1.4+dfsg-8.dsc | 5.0 KiB | 7b276ad52d083689eb02c12b0cb31d4676e9cc675c22f6add880755de347e34f |
pandas_2.1.4+dfsg.orig.tar.xz | 10.6 MiB | b516a6f52b8be6ae5461666143f0c9f9013761c26cc6109ffc7253e0b3119502 |
pandas_2.1.4+dfsg-8.debian.tar.xz | 77.0 KiB | d0cac595774cb1f012d1374665d7e6688f3ec1b649f7961526a92f3a4d78db70 |
Available diffs
- diff from 2.1.4+dfsg-7 to 2.1.4+dfsg-8 (970 bytes)
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