pandas 1.5.3+dfsg-3 source package in Ubuntu
Changelog
pandas (1.5.3+dfsg-3) unstable; urgency=medium * Tests: don't fail with fsspec 2023. (Closes: #1042043) -- Rebecca N. Palmer <email address hidden> Wed, 26 Jul 2023 07:57:11 +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 |
|---|
Downloads
| File | Size | SHA-256 Checksum |
|---|---|---|
| pandas_1.5.3+dfsg-3.dsc | 4.7 KiB | b8fef45ebf9d9dbb2520621200860b5f4d3ea3f1c7a19f07a359170a3f6a5f92 |
| pandas_1.5.3+dfsg.orig.tar.xz | 8.6 MiB | 5c50f7c36d93ed1e6e41fdd6c1116def08dadbe64245365e3410009bcbb557f3 |
| pandas_1.5.3+dfsg-3.debian.tar.xz | 69.5 KiB | efdf59700666f07339df00bc0e1f6490d5e7ed8a288d99c814e4c533af14c293 |
Available diffs
- diff from 1.5.3+dfsg-2 to 1.5.3+dfsg-3 (1.8 KiB)
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
