Result for 0002A6A83A77445E040EF33F1B70CEFA9F1B7415

Query result

Key Value
FileName./usr/lib/python3/dist-packages/pandas/io/excel/_base.py
FileSize35438
MD5AD069AF4796FC9378549145C879257A0
SHA-10002A6A83A77445E040EF33F1B70CEFA9F1B7415
SHA-256FA5DD2FC3852E24832C8F4218BD6F9AEC057EC0FA75490FEC9059681BE74B3D0
SSDEEP384:zZNkXlxxrz2fYx/T15qxxEzJGlsAoFR81do4iJo2jwl8amKm/DeGkr7Vg9C0a2pb:FNiz2f6/vhJ7edoLrKAy4F8no1p
TLSHT158F2C50BAE44123647439691889F8842C706E1AF2E14356439DCD2983F5AF2DE6FD7FC
hashlookup:parent-total2
hashlookup:trust60

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Parents (Total: 2)

The searched file hash is included in 2 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
FileSize2077440
MD5454366963DDEE10A10DA55B343F127AB
PackageDescriptiondata 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 3 version.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamepython3-pandas
PackageSectionpython
PackageVersion1.1.5+dfsg-2
SHA-1CC0C4033021573E61F2ED60F5D3B21C37D90F524
SHA-2567C4432B84D315F19AFE4CAA9151F21FB6F6B2A427C668093F3FEA37A82E5A03C
Key Value
FileSize2095828
MD5E6541380EE2E4732C3CFB039A92AB3E3
PackageDescriptiondata 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 3 version.
PackageMaintainerDebian Science Team <debian-science-maintainers@lists.alioth.debian.org>
PackageNamepython3-pandas
PackageSectionpython
PackageVersion1.1.5+dfsg-2
SHA-1079C66BF6B30AA056611617F8F627040EB47643A
SHA-25620C49A384F61BB25166DF75C418F82E2D83539ABDCE3FB0FB01F8FCC3FC2B0AA