Result for 10089ABFEF3571B136CA5A23AFF0349598B34396

Query result

Key Value
FileName./usr/lib/python3/dist-packages/xarray/tests/test_nputils.py
FileSize2257
MD50F5DE80E4908E25737595E9240852FB1
SHA-110089ABFEF3571B136CA5A23AFF0349598B34396
SHA-256C555FA47CB74F89F6E298CBA6243F0E57B9E7A720941887DF369FCA9E0FE97C5
SSDEEP48:tODFAuQh+QkQWUGIRM0HNVi6mSGzY1mG0t0ZGVyVSGGXdUdJy3i324uoX2JvDBa/:OFAuxtHUG50HNVi6mSG0UG0t0ZGVyVSg
TLSHT10D419C01421B08796363A068CA759F838503CE37550C4496B4BE44927FED55EFB3EAFA
hashlookup:parent-total17
hashlookup:trust100

Network graph view

Parents (Total: 17)

The searched file hash is included in 17 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD5B6150F9EBBA9D15D2E900DF057C00A98
PackageArchnoarch
PackageDescriptionxarray (formerly xray) is a python-pandas-like and pandas-compatible toolkit for analytics on multi-dimensional arrays. It provides N-dimensional variants of the python-pandas labeled data structures, rather than the tabular data that pandas uses. The Common Data Model for self-describing scientific data is used. The dataset is an in-memory representation of a netCDF file.
PackageNamepython3-xarray
PackageRelease2.2
PackageVersion0.17.0
SHA-1073B3164B77637D5C2A0D16E5D878F87C3D1A6E4
SHA-25612D458C1D3D1F0CCB5E42A2AFC4727C4DFD34126EF10C913ED1A6D0325838E16
Key Value
MD5533C9879FF519E3572A4A30D49ECB676
PackageArchnoarch
PackageDescriptionxarray (formerly xray) is a python-pandas-like and pandas-compatible toolkit for analytics on multi-dimensional arrays. It provides N-dimensional variants of the python-pandas labeled data structures, rather than the tabular data that pandas uses. The Common Data Model for self-describing scientific data is used. The dataset is an in-memory representation of a netCDF file.
PackageNamepython3-xarray
PackageRelease2.2
PackageVersion0.17.0
SHA-1116FC00FF71ECBB2C523FE71AE39D864E59740E0
SHA-2562688405F0E52D6617B200A54EE4C3EF6AEC21C69D1AF37D89FAD45FF32797416
Key Value
MD5D96107ED10E9FA051B6F22C852FF5FEF
PackageArchnoarch
PackageDescriptionXarray (formerly xray) is an open source project and Python package that makes working with labelled multi-dimensional arrays simple, efficient, and fun! Xarray introduces labels in the form of dimensions, coordinates and attributes on top of raw NumPy-like arrays, which allows for a more intuitive, more concise, and less error-prone developer experience. The package includes a large and growing library of domain-agnostic functions for advanced analytics and visualization with these data structures. Xarray was inspired by and borrows heavily from pandas, the popular data analysis package focused on labelled tabular data. It is particularly tailored to working with netCDF files, which were the source of xarray's data model, and integrates tightly with dask for parallel computing.
PackageMaintainerFedora Project
PackageNamepython3-xarray
PackageRelease1.fc34
PackageVersion0.17.0
SHA-121F00B9C11FE48CDFAF56940E8B1C165E5A04CC7
SHA-256F012CDBC21B445DF218451281316B64FCB894587D1A54D9E264894DDFBF8FD28
Key Value
MD5C99BB5398D9A33D028108FD41A8797CA
PackageArchnoarch
PackageDescriptionxarray (formerly xray) is a python-pandas-like and pandas-compatible toolkit for analytics on multi-dimensional arrays. It provides N-dimensional variants of the python-pandas labeled data structures, rather than the tabular data that pandas uses. The Common Data Model for self-describing scientific data is used. The dataset is an in-memory representation of a netCDF file.
PackageNamepython3-xarray
PackageRelease3.6
PackageVersion0.16.2
SHA-133716481558B3BF4F75D1BE1CE49F83FD9556A3A
SHA-2566FE5CF9C45EAEE4F6C36AF5F0F5A275F9563ECDC0A51244EDB34DFDA3389FD08
Key Value
MD5604395DDDFE74D7B8686B995AE664507
PackageArchnoarch
PackageDescriptionXarray (formerly xray) is an open source project and Python package that makes working with labelled multi-dimensional arrays simple, efficient, and fun! Xarray introduces labels in the form of dimensions, coordinates and attributes on top of raw NumPy-like arrays, which allows for a more intuitive, more concise, and less error-prone developer experience. The package includes a large and growing library of domain-agnostic functions for advanced analytics and visualization with these data structures. Xarray was inspired by and borrows heavily from pandas, the popular data analysis package focused on labelled tabular data. It is particularly tailored to working with netCDF files, which were the source of xarray's data model, and integrates tightly with dask for parallel computing.
PackageMaintainerFedora Project
PackageNamepython3-xarray
PackageRelease1.fc33
PackageVersion0.16.1
SHA-145DFB3D025A03D0F07BAA0B0B2BD1732F9161B72
SHA-2566F5C919419803326689417C03B49F01015DD59640A97EE58F793D87961055AC1
Key Value
FileSize483864
MD5D2957F7306600D8C7CCFCF337ED35BDF
PackageDescriptionN-D labeled arrays and datasets in Python 3 xarray (formerly xray) is an open source project and Python package that aims to bring the labeled data power of pandas to the physical sciences, by providing N-dimensional variants of the core pandas data structures. . It provides a pandas-like and pandas-compatible toolkit for analytics on multi-dimensional arrays, rather than the tabular data for which pandas excels. . This package provides the Python 3 library
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamepython3-xarray
PackageSectionpython
PackageVersion0.16.2-2
SHA-1591EF16D7332C34E1EB54A08389EC10740FCA162
SHA-2561301178B3D3A972B2180111721858FC7D96CBD43FB1B96FE032FCBC525FC3559
Key Value
MD54B696F8233ED269276ABBFA0DD0C4703
PackageArchnoarch
PackageDescriptionxarray (formerly xray) is a python-pandas-like and pandas-compatible toolkit for analytics on multi-dimensional arrays. It provides N-dimensional variants of the python-pandas labeled data structures, rather than the tabular data that pandas uses. The Common Data Model for self-describing scientific data is used. The dataset is an in-memory representation of a netCDF file.
PackageNamepython3-xarray
PackageRelease2.2
PackageVersion0.17.0
SHA-162C6F9C8A3D60BD3B49A1CF292CBF5397A577E2B
SHA-2560780ED1F694FBD94F79129CAE347CDB93342271C6831BA9DAA56B50E5C0D42F8
Key Value
MD522DC66200E721ECB8A63ED0F54A1AAAB
PackageArchnoarch
PackageDescriptionxarray (formerly xray) is a python-pandas-like and pandas-compatible toolkit for analytics on multi-dimensional arrays. It provides N-dimensional variants of the python-pandas labeled data structures, rather than the tabular data that pandas uses. The Common Data Model for self-describing scientific data is used. The dataset is an in-memory representation of a netCDF file.
PackageNamepython3-xarray
PackageReleaselp152.2.2
PackageVersion0.17.0
SHA-177944CE9954880375A9ED08D456AE301A607092C
SHA-256E075E28B5FB0FD155B78D5ED7367E31A0472C8025432BFA73ED3375186971EB9
Key Value
MD52E5D50BBF58C375DCEDDE73F4393C75D
PackageArchnoarch
PackageDescriptionxarray (formerly xray) is a python-pandas-like and pandas-compatible toolkit for analytics on multi-dimensional arrays. It provides N-dimensional variants of the python-pandas labeled data structures, rather than the tabular data that pandas uses. The Common Data Model for self-describing scientific data is used. The dataset is an in-memory representation of a netCDF file.
PackageNamepython3-xarray
PackageReleaselp152.43.1
PackageVersion0.16.2
SHA-1941F9947F933308B8BD6315B4C478F56DB25E7E5
SHA-256496B6498C9541606D9F03B44D6DFBA1C276E436301874A72B942BBA423CB529F
Key Value
MD56A80A55FB540A626C750DBFBE6D79B68
PackageArchnoarch
PackageDescriptionxarray (formerly xray) is a python-pandas-like and pandas-compatible toolkit for analytics on multi-dimensional arrays. It provides N-dimensional variants of the python-pandas labeled data structures, rather than the tabular data that pandas uses. The Common Data Model for self-describing scientific data is used. The dataset is an in-memory representation of a netCDF file.
PackageNamepython3-xarray
PackageReleaselp152.2.2
PackageVersion0.17.0
SHA-19575ECCA599202D84928222AD3B328A8DF1AD4A6
SHA-256F758FD4D32DC9D654ADC885091282C719D3A1EFD342990EA1779FD37B92ED52E