Parents (Total: 3)

The searched file hash is included in 3 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
FileSize	7655112
MD5	5CA98AF9A11039AB63B4646F6F4E9C85
PackageDescription	data 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.
PackageMaintainer	Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageName	python-pandas-doc
PackageSection	doc
PackageVersion	1.0.5+dfsg-3
SHA-1	859E82C01366B6B895DA269F19E4440449F95E9F
SHA-256	7D9973698376C6639C26EF9089283514F2D346AE70D8C0194BE20AA47B394D32

Key	Value
FileSize	8196480
MD5	2F510352466D48A3D3714EF384A1840D
PackageDescription	data 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.
PackageMaintainer	Debian Science Team <debian-science-maintainers@lists.alioth.debian.org>
PackageName	python-pandas-doc
PackageSection	doc
PackageVersion	1.1.5+dfsg-2
SHA-1	7E258BB2E5AC3037B382983E1D08559847A8C2B0
SHA-256	D5B984E6CE72C19E23B8703CC7ABAA231F33BDA0213023379DFE310C7F8241D7

Key	Value
FileSize	8184904
MD5	75A46F7D98F9CB59B2DB3D54A74392F3
PackageDescription	data 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.
PackageMaintainer	Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageName	python-pandas-doc
PackageSection	doc
PackageVersion	1.1.5+dfsg-2
SHA-1	05B41ABEF07C7FFB96EB3B1EAC95F1CBF6D2AABB
SHA-256	64D781FB37323CD39C44100BFA0AB071606DFFFB76269F70C2141E3710362387