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Add Python 3.10 classifier and update PyPI description
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setup.py

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#! /usr/bin/env python
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#
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# Copyright (C) 2012-2020 Michael Waskom
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# Copyright (C) 2012-2022 Michael Waskom
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DESCRIPTION = "seaborn: statistical data visualization"
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LONG_DESCRIPTION = """\
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Seaborn is a library for making statistical graphics in Python. It is built on top of `matplotlib <https://matplotlib.org/>`_ and closely integrated with `pandas <https://pandas.pydata.org/>`_ data structures.
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Seaborn is a library for making statistical graphics in Python. It is built on
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top of `matplotlib <https://matplotlib.org/>`_ and closely integrated with
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`pandas <https://pandas.pydata.org/>`_ data structures.
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Here is some of the functionality that seaborn offers:
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- A dataset-oriented API for examining relationships between multiple variables
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- Specialized support for using categorical variables to show observations or aggregate statistics
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- Options for visualizing univariate or bivariate distributions and for comparing them between subsets of data
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- Automatic estimation and plotting of linear regression models for different kinds dependent variables
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- Convenient views onto the overall structure of complex datasets
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- High-level abstractions for structuring multi-plot grids that let you easily build complex visualizations
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- Flexible data aggregation with automatic estimation and plotting of error bars
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- Multiple options for visualizing univariate or bivariate distributions
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- Estimation and plotting of linear regression models to reveal trends
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- Tools for building figures with multidimensional views onto complex dataset structure
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- Concise control over matplotlib figure styling with several built-in themes
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- Tools for choosing color palettes that faithfully reveal patterns in your data
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Seaborn aims to make visualization a central part of exploring and understanding data. Its dataset-oriented plotting functions operate on dataframes and arrays containing whole datasets and internally perform the necessary semantic mapping and statistical aggregation to produce informative plots.
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Seaborn aims to make visualization a central part of exploring and understanding
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data. Its dataset-oriented plotting functions operate on dataframes and arrays
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containing whole datasets and internally perform the necessary semantic mapping
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and statistical aggregation to produce informative plots.
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"""
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DISTNAME = 'seaborn'
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PACKAGES = [
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'seaborn',
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'seaborn.colors',
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'seaborn.external',
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'seaborn._core',
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'seaborn._marks',
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'seaborn._stats',
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'seaborn.colors',
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'seaborn.external',
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]
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CLASSIFIERS = [
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'Intended Audience :: Science/Research',
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'Programming Language :: Python :: 3.7',
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'Programming Language :: Python :: 3.8',
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'Programming Language :: Python :: 3.9',
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'Programming Language :: Python :: 3.10',
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'License :: OSI Approved :: BSD License',
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'Topic :: Scientific/Engineering :: Visualization',
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'Topic :: Multimedia :: Graphics',

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