Parents (Total: 11)

The searched file hash is included in 11 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
MD5	891CE12DB4796650C5D3112A988AC580
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	python2-seaborn
PackageRelease	bp153.1.22
PackageVersion	0.8.1
SHA-1	C42DE8D34B089AF541967F1F4604E648506230FB
SHA-256	D56324C8C42143BA3FF6E8CC836589551F6371FF643293F256D2946C6C1036AC

Key	Value
MD5	430ADFC266BD0EB4952DC9DC63E8758D
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	bp156.3.1
PackageVersion	0.8.1
SHA-1	F8962C48E6B786957C462B196D4879886D8AD244
SHA-256	215621C6D89891EC841E503A9D78BD46F4E4B36EE3438CCC156E69EFC30BA9B0

Key	Value
MD5	BCCA4174061CA0070703BF60F0CD058C
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	python2-seaborn
PackageRelease	lp150.1.4
PackageVersion	0.8.1
SHA-1	F8E341900ABF873C5D42A7145A89167D9849880B
SHA-256	80A7CCCD656D74CA4A2F041E6EDFC513F9BBC8F4F76C1106EB90B78384017534

Key	Value
MD5	4FA4D9E0C1A7222C93084DA9724EB6E4
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	bp153.1.22
PackageVersion	0.8.1
SHA-1	C1327671E93758CA5162F9BD728A6AC4A11B6475
SHA-256	F7770216185BF93FA1687F55F42F87857F3F86FE7A8AF757FD908B037E188CFC

Key	Value
MD5	A670625B5E4160F16D4015120FE53DC2
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	lp152.3.5
PackageVersion	0.8.1
SHA-1	7BC173BFA0E565DC04A2EB40414FE21C7FC847BA
SHA-256	DC818A086669403EC64CD19B6E30C71316E0339FA3A118B661FCE4FC08C17471

Key	Value
MD5	1F879E345A7410FFEBC8E98D9F5A20AB
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	python2-seaborn
PackageRelease	lp151.2.3
PackageVersion	0.8.1
SHA-1	62B02A4A78326A1BC7F6B04B26258E586FA56DE9
SHA-256	A4C7FCCAB05806D05115F046D73A3EB706A25801E8B62746DA8A4AADC61E5187

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	49967476B366C7617EEECFE954DCD47C
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	bp154.1.20
PackageVersion	0.8.1
SHA-1	09F67E0B72DA43AAEA39FF833A8FF62D342E251E
SHA-256	3A220E7B5EA8C9F018A4F2686ED40DC746EFD1F25A8B522A523BBB1B0AA5BA10

Key	Value
MD5	6A4FE8C5DCA1D10F819B98D7B0C85F87
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	bp155.2.11
PackageVersion	0.8.1
SHA-1	1B6202BB831A5E420EB85F1E74338959B9A8A51D
SHA-256	330052818AB2E499071931665322CE35D0F4AE60C8EC4641B81122E371DD03BD

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

Key	Value
MD5	F54E328CF5CBDA244A2BAD4FD4D2EA46
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	python2-seaborn
PackageRelease	lp152.3.5
PackageVersion	0.8.1
SHA-1	EAB5C23FCE3C6985F9937D5966199C7A2CB00BBE
SHA-256	7C0FFA5F3749848A1B825E9BD52D0054C108D7A541528FD79F2CB730C9709FCC