misu | High-speed physical quantities and dimensions in Python | Dataset library

by cjrh Python Version: 1.0.6 License: BSD-2-Clause

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | misu Summary

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

High-speed physical quantities and dimensions in Python

Support

Quality

Security

License

Reuse

Support

misu has a low active ecosystem.

It has 12 star(s) with 5 fork(s). There are 3 watchers for this library.

It had no major release in the last 12 months.

There are 9 open issues and 4 have been closed. On average issues are closed in 508 days. There are 2 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of misu is 1.0.6

Quality

misu has 0 bugs and 0 code smells.

Security

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

misu code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

misu is licensed under the BSD-2-Clause License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

misu releases are available to install and integrate.

Deployable package is available in PyPI.

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

It has 1324 lines of code, 72 functions and 14 files.

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

Top functions reviewed by kandi - BETA

kandi has reviewed misu and discovered the below as its top functions. This is intended to give you an instant insight into misu implemented functionality, and help decide if they suit your requirements.

Create a new quantity
Create metric prefixes
Calculate magnitude
Get unit text
Add path to sys path
Build a build for a given venv

Get all kandi verified functions for this library.

misu Key Features

No Key Features are available at this moment for misu.

misu Examples and Code Snippets

No Code Snippets are available at this moment for misu.

Community Discussions

Trending Discussions on misu

aggregate toString ignoring NA values / Concatenate rows including NAs

How do I create a randomly generated matrix with randomly generated dimension and then transpose it?

QUESTION

aggregate toString ignoring NA values / Concatenate rows including NAs

Asked 2022-Jan-16 at 04:15

Aim is to concatenate rows toString (which contain NAs) based on unique identifiers

...

ANSWER

Answered 2022-Jan-16 at 04:15

df %>%
  group_by(id, year) %>%
  summarise(across(everything(), ~toString(na.omit(.x))))

# A tibble: 3 x 4
# Groups:   id [3]
     id  year cat_1               cat_2               
                                  
1     1  2021 Too high, YOY error "YOY error"         
2     2  2021 Too high            "Too low, YOY error"
3     3  2021 Too high, YOY error ""

Source https://stackoverflow.com/questions/70727220

QUESTION

How do I create a randomly generated matrix with randomly generated dimension and then transpose it?

Asked 2020-Dec-13 at 15:59

This is what I have so far:

...

ANSWER

Answered 2020-Dec-13 at 15:59

You trying to reshape an array of shape r2 into a array of shape r1, r3 which in most case is not possible. It's like trying to arange r2 elements into a r1 x r3 grid. Your problem is over constrained. For this to work r2 needs to be equal to r1*r3.

I'm not sure what your ultimate goal is but you could just randomly get r1 and r3 and then set r2 as r1*r3. This will essentially reshape an r1*r3 arangement into shape (r1, r3).

Source https://stackoverflow.com/questions/65277317

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

Vulnerabilities

No vulnerabilities reported

Install misu

You can install using 'pip install misu' or download it from GitHub, PyPI.
You can use misu 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 .

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