Result for 003214770D338D5213CFCC77E1D4960125C7FF3D

Query result

Key Value
FileName./usr/share/doc/python-pandas-doc/html/_images/reshaping_unstack.png
FileSize53895
MD59381154FE2257867F80A6D399836FF7C
SHA-1003214770D338D5213CFCC77E1D4960125C7FF3D
SHA-2567E79E5A4752FA164F873556F38D77F948E0CAF9638EE9335996087B0333DC08D
SSDEEP1536:LyQP7BNY5iRLrcBO/3sxGTeneALdVcllWemY0qZGlzU:LvP7B7RLrcKALTveEqizU
TLSHT1DD338C37CBD62EDB6A591626A78736E1C57B016B22B95E0F1F90E9704C9F094E3F0C60
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
FileSize7600084
MD54AD1E1372BD88BF470F7EE252277458C
PackageDescriptiondocumentation and examples for pandas This package contains documentation and example scripts for python-pandas.
PackageMaintainerDebian Science Team <debian-science-maintainers@lists.alioth.debian.org>
PackageNamepython-pandas-doc
PackageSectiondoc
PackageVersion0.23.3+dfsg-3
SHA-126D541AE231CC177576B8702F8E2064AABA1A96E
SHA-256E588ECEC41FA007FA76483D04DBF604F374DB68679877EB7DAAEDD54A275152A
Key Value
FileSize8196480
MD52F510352466D48A3D3714EF384A1840D
PackageDescriptiondata structures for "relational" or "labeled" data - documentation pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. pandas is well suited for many different kinds of data: . - Tabular data with heterogeneously-typed columns, as in an SQL table or Excel spreadsheet - Ordered and unordered (not necessarily fixed-frequency) time series data. - Arbitrary matrix data (homogeneously typed or heterogeneous) with row and column labels - Any other form of observational / statistical data sets. The data actually need not be labeled at all to be placed into a pandas data structure . This package contains the documentation.
PackageMaintainerDebian Science Team <debian-science-maintainers@lists.alioth.debian.org>
PackageNamepython-pandas-doc
PackageSectiondoc
PackageVersion1.1.5+dfsg-2
SHA-17E258BB2E5AC3037B382983E1D08559847A8C2B0
SHA-256D5B984E6CE72C19E23B8703CC7ABAA231F33BDA0213023379DFE310C7F8241D7
Key Value
FileSize8184904
MD575A46F7D98F9CB59B2DB3D54A74392F3
PackageDescriptiondata structures for "relational" or "labeled" data - documentation pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. pandas is well suited for many different kinds of data: . - Tabular data with heterogeneously-typed columns, as in an SQL table or Excel spreadsheet - Ordered and unordered (not necessarily fixed-frequency) time series data. - Arbitrary matrix data (homogeneously typed or heterogeneous) with row and column labels - Any other form of observational / statistical data sets. The data actually need not be labeled at all to be placed into a pandas data structure . This package contains the documentation.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamepython-pandas-doc
PackageSectiondoc
PackageVersion1.1.5+dfsg-2
SHA-105B41ABEF07C7FFB96EB3B1EAC95F1CBF6D2AABB
SHA-25664D781FB37323CD39C44100BFA0AB071606DFFFB76269F70C2141E3710362387
Key Value
FileSize7655112
MD55CA98AF9A11039AB63B4646F6F4E9C85
PackageDescriptiondata structures for "relational" or "labeled" data - documentation pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. pandas is well suited for many different kinds of data: . - Tabular data with heterogeneously-typed columns, as in an SQL table or Excel spreadsheet - Ordered and unordered (not necessarily fixed-frequency) time series data. - Arbitrary matrix data (homogeneously typed or heterogeneous) with row and column labels - Any other form of observational / statistical data sets. The data actually need not be labeled at all to be placed into a pandas data structure . This package contains the documentation.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamepython-pandas-doc
PackageSectiondoc
PackageVersion1.0.5+dfsg-3
SHA-1859E82C01366B6B895DA269F19E4440449F95E9F
SHA-2567D9973698376C6639C26EF9089283514F2D346AE70D8C0194BE20AA47B394D32
Key Value
FileSize6939488
MD5E0650D66C28112477451D41E38787305
PackageDescriptiondata structures for "relational" or "labeled" data - documentation pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. pandas is well suited for many different kinds of data: . - Tabular data with heterogeneously-typed columns, as in an SQL table or Excel spreadsheet - Ordered and unordered (not necessarily fixed-frequency) time series data. - Arbitrary matrix data (homogeneously typed or heterogeneous) with row and column labels - Any other form of observational / statistical data sets. The data actually need not be labeled at all to be placed into a pandas data structure . This package contains the documentation.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamepython-pandas-doc
PackageSectiondoc
PackageVersion0.25.3+dfsg-7
SHA-14607CEFF250A7EC5819AD72549EB2EC7730C932B
SHA-256528FF7B697466AF9606E3BB4C1DF5033C8169E9CE8B6FB765D54A8C16B957318