numbagg | Fast N-dimensional aggregation functions with Numba | Dataset library

by shoyer Python Version: Current License: Non-SPDX

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | numbagg Summary

numbagg is a Python library typically used in Artificial Intelligence, Dataset, Numpy, Pandas applications. numbagg has no bugs, it has no vulnerabilities, it has build file available and it has low support. However numbagg has a Non-SPDX License. You can install using 'pip install numbagg' or download it from GitHub, PyPI.

Fast N-dimensional aggregation functions with Numba

Support

Quality

Security

License

Reuse

Support

numbagg has a low active ecosystem.

It has 109 star(s) with 12 fork(s). There are 5 watchers for this library.

It had no major release in the last 6 months.

There are 8 open issues and 4 have been closed. On average issues are closed in 230 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of numbagg is current.

Quality

numbagg has 0 bugs and 0 code smells.

Security

numbagg has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

numbagg code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

numbagg has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

numbagg releases are not available. You will need to build from source code and install.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

numbagg saves you 423 person hours of effort in developing the same functionality from scratch.

It has 1003 lines of code, 84 functions and 13 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi's functional review helps you automatically verify the functionalities of the libraries and avoid rework.
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of numbagg

Get all kandi verified functions for this library.

numbagg Key Features

No Key Features are available at this moment for numbagg.

numbagg Examples and Code Snippets

No Code Snippets are available at this moment for numbagg.

Community Discussions

Trending Discussions on numbagg

ModuleNotFoundError: No module named 'xarray.core.accessors'

QUESTION

ModuleNotFoundError: No module named 'xarray.core.accessors'

Asked 2019-Jul-08 at 05:06

I am new to python, and trying to run Metpy tutorial with xarray, before its ok but after I update xarray to newer version then it show an error

I have tried to create another environment in anaconda prompt, and install every module including metpy (xarray is already included)

...

ANSWER

Answered 2019-Jul-05 at 13:06

Go to C:\ProgramData\Anaconda3\envs\cobaxarray\lib\site-packages\metpy\xarray.py

find the line from xarray.core.accessors import DatetimeAccessor

change it to from xarray.core.accessor_dt import DatetimeAccessor

Source https://stackoverflow.com/questions/56902708

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install numbagg

You can install using 'pip install numbagg' or download it from GitHub, PyPI.
You can use numbagg like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

Find more information at: