Parents (Total: 7)

The searched file hash is included in 7 parent files which include package known and seen by metalookup. A sample is included below:

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

Key	Value
MD5	6B1955DC4744C3208947511A86E1B917
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	lp151.4.2
PackageVersion	0.9.0
SHA-1	FAEB623C7B20BB9C4CA51CCFF8476D1CA004324D
SHA-256	E199419EFCB620E42038AB1E425021769BE2E6721DF5CB04F084DB865FA0F136

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	E61BC6CBAFEB5CB96439CCCF670ACFA8
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	lp153.33.1
PackageVersion	0.11.1
SHA-1	7FCE61135A669CE20186F9C8EC550D1AFFF15AAC
SHA-256	2F22FF56B0EDA199D4A6DC28E5BB799F40CE7227FA7CD08B243B8B3057E8549D

Key	Value
MD5	DCA789A0E32BFF13A75D2F72AB05D9B9
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	lp152.29.1
PackageVersion	0.11.1
SHA-1	C0DD94977A096E62C179CCB4CBD536C9A1C5C586
SHA-256	1EAAAA0D9586C7BEBE570F6B14A41DE673BBC002B58581967D6EDC89367EAB4D

Key	Value
MD5	03CCDA36B3F707D49748F0EA74F06DF7
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	lp152.3.2
PackageVersion	0.11.1
SHA-1	F8DC41328A14E8139284F3CC5617F9FA8E3B14C4
SHA-256	5D822F82E9C8214BD239AB368186835AA0118F1685FCDCEE7EC68DBFAD8C8647

Key	Value
MD5	403287316ADE9A91DC3AE0CE084355D4
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	lp153.3.3
PackageVersion	0.11.1
SHA-1	B60E7B0B14809B1069BDE00A91640A08C6D9AB52
SHA-256	895145BD741E35CBB08D36E6C0BAC2D68F4C178514A49B4D7DAFD23D58CEF6BC