Result for 0F0CD1CF86977248EFD2E319EEBAAEEED17781E3

Query result

Key Value
FileName./usr/lib/python3.6/site-packages/seaborn/__pycache__/algorithms.cpython-36.pyc
FileSize6953
MD5D47F34B542AC3546A222DE191B0536A2
SHA-10F0CD1CF86977248EFD2E319EEBAAEEED17781E3
SHA-256C515378A1CA2D0F7F938F531C0C6EB01FCD77D6BB64507F2BABE00E189AA8413
SSDEEP96:rZiLW/I7VQYhXm9VyWqCCvYMzmAtydZeexFcMhLqnLyYIOw+ieorAEtVuw0NaNya:Nir5XayWLC5sdZrjRUw+xEzVvD6O
TLSHT1D7E1E9843E4096A9F8F0F4BE59DD03026764E1672388E3A3B70EA7DA6F4315A3D3425C
hashlookup:parent-total1
hashlookup:trust55

Network graph view

Parents (Total: 1)

The searched file hash is included in 1 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD56D080C6475ED40BFF24D223070927E7F
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
PackageReleaselp150.1.4
PackageVersion0.8.1
SHA-15D9B827594CF14F35E15C818FCF2EA0C1C81E0C7
SHA-2564735F819B91811458FEA65E31CA97C9E6639F25D702C1B63110CCA73CC98CCAD