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
MD5	C740BC6EED3028AB439F94C8F0AC371C
PackageArch	x86_64
PackageDescription	pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language. Python 2 version.
PackageMaintainer	CBS <cbs@centos.org>
PackageName	python2-pandas
PackageRelease	2.el7.2
PackageVersion	0.19.1
SHA-1	F99E337C3BA847840F86DD2B50B558A049C11EAE
SHA-256	CA035A4852DBE3E8AABEFF58F743B060305838610799BD0D68AD30483C886863

Key	Value
FileSize	2615560
MD5	63C959B6861897EE7516902BFE1597BA
PackageDescription	data structures for "relational" or "labeled" data 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 Python 2 version.
PackageMaintainer	NeuroDebian Team <team@neuro.debian.net>
PackageName	python-pandas
PackageSection	python
PackageVersion	0.19.2-5.1
SHA-1	EC6A749B591597AE552564152BDAF96A2FB565A2
SHA-256	0D52FEA01643C50C4A8B39B0D8BEE8F142AA8B07A56AE661EFF71522D5BCDCE9

Key	Value
FileSize	2614778
MD5	494881CCCA39595324CEE650A37A493F
PackageDescription	data structures for "relational" or "labeled" data - Python 3 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 Python 3 version.
PackageMaintainer	NeuroDebian Team <team@neuro.debian.net>
PackageName	python3-pandas
PackageSection	python
PackageVersion	0.19.2-5.1
SHA-1	44EE888F5C3FDE9C4FF13096B0F0A5551F17A735
SHA-256	44CCE0E3D7A3BCDE1E13E54F5C85AEF58D3658D5583E8441DEA85A7FD5A47267