Parents (Total: 18)

The searched file hash is included in 18 parent files which include package known and seen by metalookup. A sample is included below:

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	CA1DD84D60A3070490F95F0C640E2B2B
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.
PackageMaintainer	Fedora Project
PackageName	python3-seaborn
PackageRelease	9.fc32
PackageVersion	0.9.0
SHA-1	5254451A8880CF7EE1308F6B7578705B08E3A845
SHA-256	E6AE8D1FD7761305897D4B3C56698582A767EFBA11337C7487AB268FA8E5A16A

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	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	962B8A994AEC73A203CF682A5052B181
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
PackageName	python2-seaborn
PackageRelease	lp151.4.2
PackageVersion	0.9.0
SHA-1	79C083E1055EBA2C3E8D6B7035A7EF49D9F483AE
SHA-256	AA6450BD4EB6D6D8DDA8A9598CAB909C55178E6430E215E9995C01F1D2508397

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	479D368D927436F36DC8ADB3C5E5C060
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
PackageName	python3-seaborn
PackageRelease	4.2
PackageVersion	0.9.0
SHA-1	7CDD368A02CE9A4467BBC913E8384E37BC4DDF76
SHA-256	35C035ADF9848768106E6C3704BF70BA9C0E8874D7AC5817B37AEA5DB1F758A2

Key	Value
MD5	5495BB90AC684E369C01652E51C7D496
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
PackageName	python2-seaborn
PackageRelease	lp150.4.2
PackageVersion	0.9.0
SHA-1	868AF640C0454A1FEB5CAD620840078BAF86C922
SHA-256	E6A373CE3BC96E7635F574466475D7F6EC392A00C08D8B3FF0D9ED27AB41ECD4

Key	Value
MD5	9C8C6C7086C2D3E83A215E79E893EA99
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
PackageName	python3-seaborn
PackageRelease	lp150.4.2
PackageVersion	0.9.0
SHA-1	8C7E6377C8C2DB01FD2894E3459A7F329E77C487
SHA-256	8EF8B6ED3C0B3BCDCBD77085ED4EDB9E8FE10BFC32A66E87C2848F134ACDCC4C