Ubuntu
seaborn package

seaborn 0.13.2-3 source package in Ubuntu

Changelog

seaborn (0.13.2-3) unstable; urgency=medium

  * Remove "export PYBUILD_SYSTEM=flit" (Closes: #1067276)
  * Update 32-bit patch to make an almost equal assertion for a test

 -- Nilesh Patra <email address hidden>  Sun, 24 Mar 2024 10:33:11 +0530

Upload details

Uploaded by:
Debian Science Team
Uploaded to:
Sid
Original maintainer:
Debian Science Team
Architectures:
all
Section:
misc
Urgency:
Medium Urgency

See full publishing history Publishing

Series Pocket Published Component Section
Oracular release universe misc
Noble release universe misc

Builds

Noble: [FULLYBUILT] amd64

Downloads

File Size SHA-256 Checksum
seaborn_0.13.2-3.dsc 1.7 KiB a87434c5138a7e352f98848d77f886495a0cc885423a0c927d2edf1fa8c913c6
seaborn_0.13.2.orig.tar.gz 1.8 MiB f95141106bf1815246a3108055405c7ffe27ed69687fb3c21c754c2a7a5781c7
seaborn_0.13.2-3.debian.tar.xz 6.1 KiB a21a963854b894139c2d72fb1c0bd76e0223d4112117250d14e232e567922187

Available diffs

No changes file available.

Binary packages built by this source

python3-seaborn: statistical visualization library for Python3

 Seaborn is a library for making attractive and informative
 statistical graphics in Python. It is built on top of matplotlib and
 tightly integrated with the PyData stack, including support for numpy
 and pandas data structures and statistical routines from scipy and
 statsmodels.
 .
 Some of the features that seaborn offers are
 .
  - Several built-in themes that improve on the default matplotlib
    aesthetics
  - Tools for choosing color palettes to make beautiful plots that
    reveal patterns in your data
  - Functions for visualizing univariate and bivariate distributions
    or for comparing them between subsets of data
  - Tools that fit and visualize linear regression models for different
    kinds of independent and dependent variables
  - A function to plot statistical timeseries data with flexible estimation
    and representation of uncertainty around the estimate
  - High-level abstractions for structuring grids of plots that let you
    easily build complex visualizations
 .
 This is the Python 3 version of the package.