METADATA 5.2 KB

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  1. Metadata-Version: 2.1
  2. Name: seaborn
  3. Version: 0.13.0
  4. Summary: Statistical data visualization
  5. Author-email: Michael Waskom <mwaskom@gmail.com>
  6. Requires-Python: >=3.8
  7. Description-Content-Type: text/markdown
  8. Classifier: Intended Audience :: Science/Research
  9. Classifier: Programming Language :: Python :: 3.8
  10. Classifier: Programming Language :: Python :: 3.9
  11. Classifier: Programming Language :: Python :: 3.10
  12. Classifier: Programming Language :: Python :: 3.11
  13. Classifier: License :: OSI Approved :: BSD License
  14. Classifier: Topic :: Scientific/Engineering :: Visualization
  15. Classifier: Topic :: Multimedia :: Graphics
  16. Classifier: Operating System :: OS Independent
  17. Classifier: Framework :: Matplotlib
  18. Requires-Dist: numpy>=1.20,!=1.24.0
  19. Requires-Dist: pandas>=1.2
  20. Requires-Dist: matplotlib>=3.3,!=3.6.1
  21. Requires-Dist: pytest ; extra == "dev"
  22. Requires-Dist: pytest-cov ; extra == "dev"
  23. Requires-Dist: pytest-xdist ; extra == "dev"
  24. Requires-Dist: flake8 ; extra == "dev"
  25. Requires-Dist: mypy ; extra == "dev"
  26. Requires-Dist: pandas-stubs ; extra == "dev"
  27. Requires-Dist: pre-commit ; extra == "dev"
  28. Requires-Dist: flit ; extra == "dev"
  29. Requires-Dist: numpydoc ; extra == "docs"
  30. Requires-Dist: nbconvert ; extra == "docs"
  31. Requires-Dist: ipykernel ; extra == "docs"
  32. Requires-Dist: sphinx<6.0.0 ; extra == "docs"
  33. Requires-Dist: sphinx-copybutton ; extra == "docs"
  34. Requires-Dist: sphinx-issues ; extra == "docs"
  35. Requires-Dist: sphinx-design ; extra == "docs"
  36. Requires-Dist: pyyaml ; extra == "docs"
  37. Requires-Dist: pydata_sphinx_theme==0.10.0rc2 ; extra == "docs"
  38. Requires-Dist: scipy>=1.7 ; extra == "stats"
  39. Requires-Dist: statsmodels>=0.12 ; extra == "stats"
  40. Project-URL: Docs, http://seaborn.pydata.org
  41. Project-URL: Source, https://github.com/mwaskom/seaborn
  42. Provides-Extra: dev
  43. Provides-Extra: docs
  44. Provides-Extra: stats
  45. <img src="https://raw.githubusercontent.com/mwaskom/seaborn/master/doc/_static/logo-wide-lightbg.svg"><br>
  46. --------------------------------------
  47. seaborn: statistical data visualization
  48. =======================================
  49. [![PyPI Version](https://img.shields.io/pypi/v/seaborn.svg)](https://pypi.org/project/seaborn/)
  50. [![License](https://img.shields.io/pypi/l/seaborn.svg)](https://github.com/mwaskom/seaborn/blob/master/LICENSE)
  51. [![DOI](https://joss.theoj.org/papers/10.21105/joss.03021/status.svg)](https://doi.org/10.21105/joss.03021)
  52. [![Tests](https://github.com/mwaskom/seaborn/workflows/CI/badge.svg)](https://github.com/mwaskom/seaborn/actions)
  53. [![Code Coverage](https://codecov.io/gh/mwaskom/seaborn/branch/master/graph/badge.svg)](https://codecov.io/gh/mwaskom/seaborn)
  54. Seaborn is a Python visualization library based on matplotlib. It provides a high-level interface for drawing attractive statistical graphics.
  55. Documentation
  56. -------------
  57. Online documentation is available at [seaborn.pydata.org](https://seaborn.pydata.org).
  58. 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.
  59. To build the documentation locally, please refer to [`doc/README.md`](doc/README.md).
  60. Dependencies
  61. ------------
  62. Seaborn supports Python 3.8+.
  63. 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/).
  64. Installation
  65. ------------
  66. The latest stable release (and required dependencies) can be installed from PyPI:
  67. pip install seaborn
  68. It is also possible to include optional statistical dependencies:
  69. pip install seaborn[stats]
  70. Seaborn can also be installed with conda:
  71. conda install seaborn
  72. Note that the main anaconda repository lags PyPI in adding new releases, but conda-forge (`-c conda-forge`) typically updates quickly.
  73. Citing
  74. ------
  75. 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.
  76. Testing
  77. -------
  78. Testing seaborn requires installing additional dependencies; they can be installed with the `dev` extra (e.g., `pip install .[dev]`).
  79. 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.
  80. 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.
  81. Development
  82. -----------
  83. Seaborn development takes place on Github: https://github.com/mwaskom/seaborn
  84. 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).