118 lines
5.3 KiB
Plaintext
118 lines
5.3 KiB
Plaintext
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Metadata-Version: 2.1
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Name: seaborn
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Version: 0.13.2
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Summary: Statistical data visualization
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Author-email: Michael Waskom <mwaskom@gmail.com>
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Requires-Python: >=3.8
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Description-Content-Type: text/markdown
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Classifier: Intended Audience :: Science/Research
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Classifier: Programming Language :: Python :: 3.8
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Classifier: Programming Language :: Python :: 3.9
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Classifier: Programming Language :: Python :: 3.10
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Classifier: Programming Language :: Python :: 3.11
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Classifier: Programming Language :: Python :: 3.12
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Classifier: License :: OSI Approved :: BSD License
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Classifier: Topic :: Scientific/Engineering :: Visualization
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Classifier: Topic :: Multimedia :: Graphics
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Classifier: Operating System :: OS Independent
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Classifier: Framework :: Matplotlib
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Requires-Dist: numpy>=1.20,!=1.24.0
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Requires-Dist: pandas>=1.2
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Requires-Dist: matplotlib>=3.4,!=3.6.1
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Requires-Dist: pytest ; extra == "dev"
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Requires-Dist: pytest-cov ; extra == "dev"
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Requires-Dist: pytest-xdist ; extra == "dev"
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Requires-Dist: flake8 ; extra == "dev"
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Requires-Dist: mypy ; extra == "dev"
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Requires-Dist: pandas-stubs ; extra == "dev"
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Requires-Dist: pre-commit ; extra == "dev"
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Requires-Dist: flit ; extra == "dev"
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Requires-Dist: numpydoc ; extra == "docs"
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Requires-Dist: nbconvert ; extra == "docs"
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Requires-Dist: ipykernel ; extra == "docs"
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Requires-Dist: sphinx<6.0.0 ; extra == "docs"
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Requires-Dist: sphinx-copybutton ; extra == "docs"
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Requires-Dist: sphinx-issues ; extra == "docs"
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Requires-Dist: sphinx-design ; extra == "docs"
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Requires-Dist: pyyaml ; extra == "docs"
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Requires-Dist: pydata_sphinx_theme==0.10.0rc2 ; extra == "docs"
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Requires-Dist: scipy>=1.7 ; extra == "stats"
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Requires-Dist: statsmodels>=0.12 ; extra == "stats"
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Project-URL: Docs, http://seaborn.pydata.org
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Project-URL: Source, https://github.com/mwaskom/seaborn
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Provides-Extra: dev
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Provides-Extra: docs
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Provides-Extra: stats
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<img src="https://raw.githubusercontent.com/mwaskom/seaborn/master/doc/_static/logo-wide-lightbg.svg"><br>
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--------------------------------------
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seaborn: statistical data visualization
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=======================================
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[](https://pypi.org/project/seaborn/)
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[](https://github.com/mwaskom/seaborn/blob/master/LICENSE.md)
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[](https://doi.org/10.21105/joss.03021)
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[](https://github.com/mwaskom/seaborn/actions)
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[](https://codecov.io/gh/mwaskom/seaborn)
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Seaborn is a Python visualization library based on matplotlib. It provides a high-level interface for drawing attractive statistical graphics.
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Documentation
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-------------
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Online documentation is available at [seaborn.pydata.org](https://seaborn.pydata.org).
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The docs include a [tutorial](https://seaborn.pydata.org/tutorial.html), [example gallery](https://seaborn.pydata.org/examples/index.html), [API reference](https://seaborn.pydata.org/api.html), [FAQ](https://seaborn.pydata.org/faq), and other useful information.
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To build the documentation locally, please refer to [`doc/README.md`](doc/README.md).
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Dependencies
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------------
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Seaborn supports Python 3.8+.
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Installation requires [numpy](https://numpy.org/), [pandas](https://pandas.pydata.org/), and [matplotlib](https://matplotlib.org/). Some advanced statistical functionality requires [scipy](https://www.scipy.org/) and/or [statsmodels](https://www.statsmodels.org/).
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Installation
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------------
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The latest stable release (and required dependencies) can be installed from PyPI:
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pip install seaborn
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It is also possible to include optional statistical dependencies:
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pip install seaborn[stats]
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Seaborn can also be installed with conda:
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conda install seaborn
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Note that the main anaconda repository lags PyPI in adding new releases, but conda-forge (`-c conda-forge`) typically updates quickly.
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Citing
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------
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A paper describing seaborn has been published in the [Journal of Open Source Software](https://joss.theoj.org/papers/10.21105/joss.03021). The paper provides an introduction to the key features of the library, and it can be used as a citation if seaborn proves integral to a scientific publication.
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Testing
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-------
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Testing seaborn requires installing additional dependencies; they can be installed with the `dev` extra (e.g., `pip install .[dev]`).
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To test the code, run `make test` in the source directory. This will exercise the unit tests (using [pytest](https://docs.pytest.org/)) and generate a coverage report.
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Code style is enforced with `flake8` using the settings in the [`setup.cfg`](./setup.cfg) file. Run `make lint` to check. Alternately, you can use `pre-commit` to automatically run lint checks on any files you are committing: just run `pre-commit install` to set it up, and then commit as usual going forward.
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Development
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-----------
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Seaborn development takes place on Github: https://github.com/mwaskom/seaborn
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Please submit bugs that you encounter to the [issue tracker](https://github.com/mwaskom/seaborn/issues) with a reproducible example demonstrating the problem. Questions about usage are more at home on StackOverflow, where there is a [seaborn tag](https://stackoverflow.com/questions/tagged/seaborn).
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