seaborn 0.10.0-1 source package in Ubuntu

Changelog

seaborn (0.10.0-1) unstable; urgency=medium

  * Team Upload.
  * New upstream version 0.10.0
    Closes: #950695, #950928, #897263
  * Add "Rules-Requires-Root:no"
  * Add upstream/metadata
  * Drop compat, switch to debhelper-compat
  * Remove un-needed patch
  * Modify patch wrt new version
  * Bump standards version to 4.5.0
  * Fix copyright

 -- Nilesh Patra <email address hidden>  Wed, 26 Feb 2020 09:41:20 +0000

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
Focal release universe misc

Builds

Focal: [FULLYBUILT] amd64

Downloads

File Size SHA-256 Checksum
seaborn_0.10.0-1.dsc 2.2 KiB 6e901ce84c478aaa24864971b523c176bcf7f39c886eb7d5e623b5fa0854077c
seaborn_0.10.0.orig.tar.gz 277.7 KiB 37e2c7783ef2bb12ce749783870ca740750fc7cc0bd1776c6cacab19514affbd
seaborn_0.10.0-1.debian.tar.xz 5.3 KiB dbb019da95f83aaf667c752fff0689532b3a6b83a473d7c47682f6abbbc0640c

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.