Result for 15670075BD76FED56347BB961E603273FEEB944D

Query result

Key Value
FileName./usr/lib/python3.6/site-packages/seaborn/tests/__pycache__/test_algorithms.cpython-36.pyc
FileSize7550
MD578492263E7DE05FC42545D8A5BA38F87
SHA-115670075BD76FED56347BB961E603273FEEB944D
SHA-2562D803B00884A268CFF11B0CF044024AC46152716974FB8B2BDBD8D4EC443430F
SSDEEP96:eXonaYkkIRachqqaBbk+J3TbnuAG3nxO1U65l2LvWZBkzf1p+y9klVSckUrpsptZ:7IRaJJDbnKh6mTpzdky98VSck3ptDKY
TLSHT133F1964C7F420F86FE36F1BC904903182775E3352BDAC37B1935626EAD072952E71A9A
hashlookup:parent-total5
hashlookup:trust75

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Parents (Total: 5)

The searched file hash is included in 5 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD5430ADFC266BD0EB4952DC9DC63E8758D
PackageArchnoarch
PackageDescriptionSeaborn 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
PackageMaintainerhttps://bugs.opensuse.org
PackageNamepython3-seaborn
PackageReleasebp156.3.1
PackageVersion0.8.1
SHA-1F8962C48E6B786957C462B196D4879886D8AD244
SHA-256215621C6D89891EC841E503A9D78BD46F4E4B36EE3438CCC156E69EFC30BA9B0
Key Value
MD54FA4D9E0C1A7222C93084DA9724EB6E4
PackageArchnoarch
PackageDescriptionSeaborn 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
PackageMaintainerhttps://bugs.opensuse.org
PackageNamepython3-seaborn
PackageReleasebp153.1.22
PackageVersion0.8.1
SHA-1C1327671E93758CA5162F9BD728A6AC4A11B6475
SHA-256F7770216185BF93FA1687F55F42F87857F3F86FE7A8AF757FD908B037E188CFC
Key Value
MD5A670625B5E4160F16D4015120FE53DC2
PackageArchnoarch
PackageDescriptionSeaborn 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
PackageMaintainerhttps://bugs.opensuse.org
PackageNamepython3-seaborn
PackageReleaselp152.3.5
PackageVersion0.8.1
SHA-17BC173BFA0E565DC04A2EB40414FE21C7FC847BA
SHA-256DC818A086669403EC64CD19B6E30C71316E0339FA3A118B661FCE4FC08C17471
Key Value
MD549967476B366C7617EEECFE954DCD47C
PackageArchnoarch
PackageDescriptionSeaborn 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
PackageMaintainerhttps://bugs.opensuse.org
PackageNamepython3-seaborn
PackageReleasebp154.1.20
PackageVersion0.8.1
SHA-109F67E0B72DA43AAEA39FF833A8FF62D342E251E
SHA-2563A220E7B5EA8C9F018A4F2686ED40DC746EFD1F25A8B522A523BBB1B0AA5BA10
Key Value
MD56A4FE8C5DCA1D10F819B98D7B0C85F87
PackageArchnoarch
PackageDescriptionSeaborn 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
PackageMaintainerhttps://bugs.opensuse.org
PackageNamepython3-seaborn
PackageReleasebp155.2.11
PackageVersion0.8.1
SHA-11B6202BB831A5E420EB85F1E74338959B9A8A51D
SHA-256330052818AB2E499071931665322CE35D0F4AE60C8EC4641B81122E371DD03BD