Parents (Total: 2)

The searched file hash is included in 2 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
MD5	EE7B90C81C78AF3C406D9ABCC4AD32B4
PackageArch	noarch
PackageDescription	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: - 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
PackageMaintainer	https://bugs.opensuse.org
PackageName	python3-seaborn
PackageRelease	lp151.2.3
PackageVersion	0.8.1
SHA-1	B2558ACD51673F2754C6AA435E68E2FE92B928FD
SHA-256	ACD804EA72BF03B7C91CDE3C6601A661E6A8A4C405EB1180CD3C195B84F86ABE

Key	Value
MD5	6D080C6475ED40BFF24D223070927E7F
PackageArch	noarch
PackageDescription	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: - 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
PackageMaintainer	https://bugs.opensuse.org
PackageName	python3-seaborn
PackageRelease	lp150.1.4
PackageVersion	0.8.1
SHA-1	5D9B827594CF14F35E15C818FCF2EA0C1C81E0C7
SHA-256	4735F819B91811458FEA65E31CA97C9E6639F25D702C1B63110CCA73CC98CCAD