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Statistical data visualization using matplotlib
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MaozGelbart MNT: Remove unused code paths (#1965)
* TST: pandas==1.0 compat

* Remove old matplotlib paths

* Remove old scipy paths

* Remove _set_spine_position

The behavior that this function addressed has been resolved in matplotlib 1.4:

* Clean more old compat code paths

Removed a few try/except clauses aimed to cover old matplotlib/pandas
versions that are no longer supported.

* Remove __future__ imports

* Improve code style
Latest commit 5498cdb Feb 27, 2020


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.github Fix/update some links in the docs Apr 11, 2018
doc MNT: Remove unused code paths (#1965) Feb 27, 2020
examples Fix thumbnail on gallery page Jan 19, 2020
licences Excise six Jan 22, 2020
seaborn MNT: Remove unused code paths (#1965) Feb 27, 2020
testing Modernize minimal dependencies Jan 22, 2020
.coveragerc Move color dictionaries to submodule and don't evaluate coverage Sep 30, 2017
.gitignore Ignore new pytest cache directory Jun 17, 2018
.mailmap ENH: to make two Michaels into one Mar 25, 2014
.travis.yml Drop 2.7 (and 3.5) from travis build Jan 22, 2020
LICENSE Update dates Jan 18, 2020 Remove doc and examples from pypi source files Dec 2, 2014
Makefile Include tests in lint check Jan 19, 2020 Tweak release notes Jan 24, 2020
pytest.ini Remove seaborn.apionly Jan 22, 2020
requirements.txt Update to explicitly declare dependencies for pip May 12, 2018
setup.cfg Drop Python 2 from setup files Jan 22, 2020 Bump version back to dev on master Jan 24, 2020

seaborn: statistical data visualization

PyPI Version License DOI Build Status Code Coverage

Seaborn is a Python visualization library based on matplotlib. It provides a high-level interface for drawing attractive statistical graphics.


Online documentation is available at

The docs include a tutorial, example gallery, API reference, and other useful information.


Seaborn supports Python 3.6+ and no longer supports Python 2.

Installation requires numpy, scipy, pandas, and matplotlib. Some functions will optionally use statsmodels if it is installed.


The latest stable release (and older versions) can be installed from PyPI:

pip install seaborn

You may instead want to use the development version from Github:

pip install git+


To test the code, run make test in the source directory. This will exercise both the unit tests and docstring examples (using pytest).

The doctests require a network connection (unless all example datasets are cached), but the unit tests can be run offline with make unittests. Run make coverage to generate a test coverage report and make lint to check code style consistency.


Seaborn development takes place on Github:

Please submit bugs that you encounter to the issue tracker with a reproducible example demonstrating the problem. Questions about usage are more at home on StackOverflow, where there is a seaborn tag.

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