Parents (Total: 12)

The searched file hash is included in 12 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
FileName	https://ftp.lysator.liu.se/pub/OpenBSD/6.9/packages//powerpc64//py3-seaborn-0.11.1.tgz
MD5	794844A88BA00B95937F6580BF67227F
SHA-1	AE399CD6A720292A0AD737B2D3037FBC415DDBAE
SHA-256	B2812BFFBFB8C5B5CA0AC3E4AA3FD6E3FDDA84177B3FB4C21E323744EA846DAF
SSDEEP	12288:6SbG7aFVRQvBQjwe5XPp+QXT7+b+Cd0dFQd5fYWw55z6XiFXix+UF:6SbG7u8msmXPgQ3S7Rt1Xm05F
TLSH	T163D423251EF0F314B467A577A9332FC7F214CA87DAD1A64314EDE4B2CC0A947019AAAD

Key	Value
FileName	https://ftp.lysator.liu.se/pub/OpenBSD/6.9/packages//mips64//py3-seaborn-0.11.1.tgz
MD5	41082A829B546BAF13C5CE2785E2BF77
SHA-1	BBE7594FAB50CD543F76DC1803B04CC421BEB3F9
SHA-256	0B45F451D8997DF9B9C404DD2E15F251BBB6B5F3A28D9366D3DBF41678C5BF48
SSDEEP	12288:JXzG7aFVRQvBQjwe5XPp+QXT7j7KC8Qd5fx21jrpAnyy9Xox+UF:JjG7u8msmXPgQ3BtxyY9a5F
TLSH	T179D423785EB9F248E43AB4AF49337E96A2004EDBDCF1A60A58D9E0C0975EC4241CDDDD

Key	Value
FileSize	206196
MD5	1111536A43BF26A5E491913FEA21AD8B
PackageDescription	statistical visualization library for Python3 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.
PackageMaintainer	Debian Science Maintainers <debian-science-maintainers@lists.alioth.debian.org>
PackageName	python3-seaborn
PackageSection	python
PackageVersion	0.11.1-1
SHA-1	C55A763C9B479176CF8B1B3DFB79DBCFAA10511B
SHA-256	70C265844756F4F6EF2A4C3D62521D6EC4B445F190023EBAFA730AD547CE0974

Key	Value
FileName	https://ftp.lysator.liu.se/pub/OpenBSD/6.9/packages//arm//py3-seaborn-0.11.1.tgz
MD5	1CBB84A9D807D87950D7000F6E7980D6
SHA-1	FBABEFE113011F48155304D38110F5C6CC492FD3
SHA-256	9719C35078B7A63D07BFCAAD3D6A98FA294E02F7087A18E711EF8F04948F9C21
SSDEEP	12288:6frQXG7aFVRQvBQjwe5GVClSXT7+b+Cd0dFQd5fYWw55z6XiFXix+UF:urQXG7u8msmGVClS3S7Rt1Xm05F
TLSH	T16AD4236419E0F354A53750B7A9372BC3F214ADC3EFC12B5205DEB4FDC826847429D66A

Key	Value
FileName	http://archlinux.mirror.root.lu//pool//community//python-seaborn-0.11.1-1-any.pkg.tar.zst
MD5	7903E9BA3192716440D6C3856CF16CB0
SHA-1	E519A38E72C48567A94EDA01231D2B26F881C566
SHA-256	0315FBA6E4A29915C18338255081B2F7B259D0F9D381903B2F544E6901712F5C
SSDEEP	12288:+RC0Gw9nbvCv7mSW83Ci30mlDKnrsUrY4yrU:+RhvCv9W8ZJlDSsUEjrU
TLSH	T1CFB423006366B880A2266127FAA50B33772DF7D75FD321DA398278936C4FD710F916E9

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
FileName	https://ftp.lysator.liu.se/pub/OpenBSD/6.9/packages//i386//py3-seaborn-0.11.1.tgz
MD5	BE1EA5ADF0EF2BDF5D8BF6BD49BF16B3
SHA-1	F3F62F700768444653136A73E1888BAD593E4ADA
SHA-256	25F68D7FD528D342DE3E0BF21300E954E8C3D7F997D36DB81F2FE413969A9D74
SSDEEP	12288:kakG7aFVRQvBQjwe5XPp+QXT7+b+Cd0dFQd5fYWw55z6XiFXix+UF:kjG7u8msmXPgQ3S7Rt1Xm05F
TLSH	T1EBD423281FF0F304B527A57BA9332EC3F2249A97E9E1974215ECE4B1CC0E9474199A6D

Key	Value
FileName	https://ftp.lysator.liu.se/pub/OpenBSD/6.9/packages//mips64el//py3-seaborn-0.11.1.tgz
MD5	FED05D66B1ED6E11514F83414F7BAC66
SHA-1	0C1D50B7A919F6E4367079B6493FC5F4EEB998C7
SHA-256	3657339E039A0DB635130226CF94FEC61945976772820D448908F9AB67A01D6C
SSDEEP	12288:QIeiG7aFVRQvBQjwe5GVClSXT7j7KC8Qd5fx21jrpAnyy9Xox+UF:QViG7u8msmGVClS3BtxyY9a5F
TLSH	T16CD423346DE4F248F13B74EB9D273DC6A1004ECBEDA429060DEAE0E597AAC4142DD9DD

Key	Value
FileName	https://ftp.lysator.liu.se/pub/OpenBSD/6.9/packages//sparc64//py3-seaborn-0.11.1.tgz
MD5	40661AE586D4CE5EF73A08AB3F40EB8F
SHA-1	088673F9592B271673557080000D8EAAF2E0D33A
SHA-256	CCF627C7E17DF4A09F251D870A6B8A12EAC59A44CE859AEB492E91A806E1342F
SSDEEP	12288:Ua/G7aFVRQvBQjwe5GVClSXT7j7KC8Qd5fx21jrpAnyy9Xox+UF:Ua/G7u8msmGVClS3BtxyY9a5F
TLSH	T1A7D423746CF4F258E13770AB9D373EC6A1004ECBEDE529050DDAE0E493AAC42419DADE

Key	Value
FileName	https://ftp.lysator.liu.se/pub/OpenBSD/6.9/packages//powerpc//py3-seaborn-0.11.1.tgz
MD5	E18402B2EF470C1441D91E67CAB9648D
SHA-1	8B42966D5668E39F592BB774837425EFB3244544
SHA-256	04C7384E3866D70D764DCF229D93281F9BB197E3DFADF3259FAAA9FCDBDCD743
SSDEEP	12288:9fG7aFVRQvBQjwe5XPp+QXT7+b+Cd0dFQd5fYWw55z6XiFXix+UF:9fG7u8msmXPgQ3S7Rt1Xm05F
TLSH	T162D423241EF0F3147427A977A8332FC3E2148ED7EAE1A71214DDE4B1CC0E947459AAAD

Key	Value
FileSize	205760
MD5	E1895E1BE0C3319D32D0C131AA9EB6F0
PackageDescription	statistical visualization library for Python3 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.
PackageMaintainer	Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageName	python3-seaborn
PackageSection	python
PackageVersion	0.11.1-1
SHA-1	22A01F183EA134F7F7E9A89D595BF125390F1C1B
SHA-256	FFFC71E019C2B68D90E40C818E6CCEA1BE365A50F1C592C782AACAEE8FA3D7B3

Key	Value
FileName	https://ftp.lysator.liu.se/pub/OpenBSD/6.9/packages//amd64//py3-seaborn-0.11.1.tgz
MD5	7F5085464B9E87D8876C7613B934AF2A
SHA-1	A611A61A960E5B4FB1D622416D8F5BE544E07B45
SHA-256	0A48307CADFA979E82D17A03CE2FCA20492218B15EB832695ADD3D8C7A8A1D7F
SSDEEP	12288:5STWG7aFVRQvBQjwe5GVClSXT7+b+Cd0dFQd5fYWw55z6XiFXix+UF:wCG7u8msmGVClS3S7Rt1Xm05F
TLSH	T14DD433241DB0F354B13754B7A9371BC3F214ADC3EEC0374206EEA4BAC96AC474199A6E