Result for 072D75FA0BE869BE7A2D0EC9E3A424820426A169

Query result

Key Value
FileName./usr/lib/python3/dist-packages/seaborn/categorical.py
FileSize133468
MD57DB95D8FBDF8D25ED87DD09D578E0903
SHA-1072D75FA0BE869BE7A2D0EC9E3A424820426A169
SHA-256F0330A6C623D8DD3E5211332CF597613ABC1648213D2846C480D40F72A0E28F9
SSDEEP1536:SFOiDk7yDs1KWqccYFxK9UH/E4SLySjVbGcl8DEPdKb2fYuvd+tbdth5Fa4YqTMj:1iIqNa1cl+ElKb9uvObnFaDqTMj
TLSHT178D3A55BEE180A278783D8A855DBD447D724B5174A8926783CEC93480F8593C9AFCFEC
hashlookup:parent-total2
hashlookup:trust60

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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
FileSize128234
MD508D39043EEABBBEEDF59D6797A495D6D
PackageDescriptionstatistical visualization library 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 - 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 . This is the Python 2 version of the package.
PackageMaintainerDebian Science Maintainers <debian-science-maintainers@lists.alioth.debian.org>
PackageNamepython-seaborn
PackageSectionpython
PackageVersion0.7.1-4
SHA-169794894E3AE83CABFEEEC8F9110B7E1A74484BD
SHA-256D24A23C2F5B4B93DA6586A63BB4C7148CBEAA76201670A93BD516EDD0A46EC4E
Key Value
FileSize128348
MD5C56C0DAED54455F32081A7D2AE88798B
PackageDescriptionstatistical visualization library 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 - 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 . This is the Python 3 version of the package.
PackageMaintainerDebian Science Maintainers <debian-science-maintainers@lists.alioth.debian.org>
PackageNamepython3-seaborn
PackageSectionpython
PackageVersion0.7.1-4
SHA-1C2A4C4A557A93A817290CD64A6B5CD2B17BD654E
SHA-2562A8A424586909A5C4C00FF964D5FDD0C1A8FA175F9476110636462D7BED0337A