dev-python/seaborn: bump to 0.8.1
Package-Manager: Portage-2.3.40, Repoman-2.3.9
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dev-python/seaborn/metadata.xml
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36
dev-python/seaborn/metadata.xml
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<?xml version="1.0" encoding="UTF-8"?>
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<!DOCTYPE pkgmetadata SYSTEM "http://www.gentoo.org/dtd/metadata.dtd">
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<pkgmetadata>
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<maintainer type="person">
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<email>horea.christ@gmail.com</email>
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<name>Horea Christian</name>
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</maintainer>
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<maintainer type="project">
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<email>proxy-maint@gentoo.org</email>
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<name>Proxy Maintainers</name>
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</maintainer>
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<maintainer type="project">
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<email>python@gentoo.org</email>
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<name>Python</name>
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</maintainer>
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<longdescription lang="en">
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Seaborn is a library for making attractive and informative statistical graphics
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in Python. It is built on top of matplotlib and tightly integrated with the
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PyData stack, including support for numpy and pandas data structures and
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statistical routines from scipy and statsmodels.
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Some of the features that seaborn offers are
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* Several built-in themes that improve on the default matplotlib aesthetics
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* Tools for choosing color palettes to make beautiful plots that reveal patterns in your data
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* Functions for visualizing univariate and bivariate distributions or for comparing them between subsets of data
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* Tools that fit and visualize linear regression models for different kinds of independent and dependent variables
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* Functions that visualize matrices of data and use clustering algorithms to discover structure in those matrices
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* A function to plot statistical timeseries data with flexible estimation and representation of uncertainty around the estimate
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* High-level abstractions for structuring grids of plots that let you easily build complex visualizations
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</longdescription>
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<upstream>
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<remote-id type="pypi">seaborne</remote-id>
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<remote-id type="github">mwaskom/seaborn</remote-id>
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</upstream>
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</pkgmetadata>
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