Result for 001A29DEDADDD7CBAF7503A8E04CA7EB88D0BB48

Query result

Key Value
FileName./usr/lib/python3/dist-packages/pandas/core/categorical.py
FileSize7869
MD57A55B43F76169A5DD1D2E79171ECA943
SHA-1001A29DEDADDD7CBAF7503A8E04CA7EB88D0BB48
SHA-256065C4006E5F3A2E6A55E35AC6D7F3DD4F682F19718090C45B486CA19B703A973
SSDEEP192:vaiBetAwqnE91y16nf+Iu6hVo/ziOOIuVm72PKS+:stvqg1y1uPlOsVOR
TLSHT132F1423A2D8D542AC313C8B445DE9903E6696707560C34F4F8BD2F502FCBA24A6BCACD
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
FileSize1076560
MD521DBCDB793BF0D89F72DEDD75127B670
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 2 version.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamepython-pandas
PackageSectionpython
PackageVersion0.13.1-2ubuntu2
SHA-183C388B6E02E63AD7FA6E369570C2F6152FA68C6
SHA-2562F3045690338C212290E9704EAD486BF98B77FA681A704B7768AC7BBB6DEBF62
Key Value
FileSize1074354
MD5B6CD81482874CA523AF71F566D38233A
PackageDescriptiondata 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.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamepython3-pandas
PackageSectionpython
PackageVersion0.13.1-2ubuntu2
SHA-117251B3EB88427B78B25464F111F3CFE005A76CC
SHA-2560E6C32A77FEAF3A5C4B4AC949356A91A08DEBFA9078B2255A20ADF7176A0FCE0