Key | Value |
---|---|
FileName | ./usr/lib/python3/dist-packages/pandas/tseries/tests/test_resample.py |
FileSize | 121702 |
MD5 | 90049217F34CB6168E618E51874089F5 |
SHA-1 | 050CD160EA209CAC0C0007CBF80EF73C74A2DA87 |
SHA-256 | 5EF13BBEBACAC2C85A89AF965B102206A5057F3C023520CE620A4973349AD0EF |
SSDEEP | 3072:Tq7Mte7YcXQ2lAC4ov/n2aE9UwHLS4drXVlougoDQuw7i:27M+XQ2l/v+1r39XVlougoDQuw7i |
TLSH | T102C3754159560929A383A5BD846E9E8BD70BF5938C8918907AEC51401FCC13CFBEEFF9 |
hashlookup:parent-total | 2 |
hashlookup:trust | 60 |
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 |
---|---|
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 |