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DIST pandas-0.15.1.tar.gz 4508211 SHA256 6c15aebaf10a02fa411f336d2029fb303892b17d470f5d7de91597fc31cebd65 SHA512 2485c06a3fdf4bec479ed4a633901041283737f203ca1ab92130fbbd0236bd2198513079012e9af4c735768c8c2a70a477e3841e382661cb11d7ae00f6d72dce WHIRLPOOL 67a1cdaae88e6f5735d513d96471b2667e8f028c17f1708cfb2c8a64e0485ab2d2636fd65fc5b163f2b916b80374d660d1d6c20e7a1662112559cae1ddef0aa1 | ||
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DIST seaborn-0.5.1.tar.gz 104426 SHA256 8c8f7f1036cf6155be3d987ee23d2eeeed8c272b0803b32b7d524614f8526688 SHA512 bbcdf0625e096b8f41d56521f3e319a64d82632131d80ed1e81144362fe881d9b5df4d3b5a5fa09363b1782897d9ac68d3fc647d82da4e0017c5dba21c897b8d WHIRLPOOL 682a32f2d40a742e87659f27a675c437875a4b4dfcfd8195b774c49ae38f5ad73ee4b73aa00dabab33ccb6015e5eb5326605c897c8b1cac341cc9db0d6143f73 |
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<?xml version="1.0" encoding="UTF-8"?> | ||
<!DOCTYPE pkgmetadata SYSTEM "http://www.gentoo.org/dtd/metadata.dtd"> | ||
<pkgmetadata> | ||
<herd>python</herd> | ||
<maintainer> | ||
<email>[email protected]</email> | ||
<name>Justin Lecher</name> | ||
</maintainer> | ||
<longdescription lang="en"> | ||
Seaborn is a library for making attractive and informative statistical graphics | ||
in Python. It is built on top of matplotlib and tightly integrated with the | ||
PyData stack, including support for numpy and pandas data structures and | ||
statistical routines from scipy and statsmodels. | ||
|
||
Some of the features that seaborn offers are | ||
|
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* Several built-in themes that improve on the default matplotlib aesthetics | ||
* Tools for choosing color palettes to make beautiful plots that reveal | ||
patterns in your data | ||
* Functions for visualizing univariate and bivariate distributions or for | ||
comparing them between subsets of data | ||
* Tools that fit and visualize linear regression models for different kinds | ||
of independent and dependent variables | ||
* Functions that visualize matrices of data and use clustering algorithms to | ||
discover structure in those matrices | ||
* A function to plot statistical timeseries data with flexible estimation and | ||
representation of uncertainty around the estimate | ||
* High-level abstractions for structuring grids of plots that let you easily | ||
build complex visualizations | ||
</longdescription> | ||
<upstream> | ||
<remote-id type="pypi">seaborne</remote-id> | ||
<remote-id type="github">mwaskom/seaborn</remote-id> | ||
</upstream> | ||
</pkgmetadata> |
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