supervenn | supervenn : precise and easy-to-read multiple sets | Computer Vision library

by gecko984 Python Version: 0.5.0 License: MIT

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

kandi X-RAY | supervenn Summary

supervenn is a Python library typically used in Artificial Intelligence, Computer Vision, Example Codes applications. supervenn 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 supervenn' or download it from GitHub, PyPI.

supervenn: precise and easy-to-read multiple sets visualization in Python

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Quality

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supervenn has a low active ecosystem.

It has 233 star(s) with 17 fork(s). There are 8 watchers for this library.

There were 1 major release(s) in the last 12 months.

There are 9 open issues and 18 have been closed. On average issues are closed in 34 days. There are 3 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of supervenn is 0.5.0

Quality

supervenn has 0 bugs and 0 code smells.

Security

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

supervenn code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

supervenn is licensed under the MIT License. This license is Permissive.

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

Reuse

supervenn releases are available to install and integrate.

Deployable package is available in PyPI.

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

Installation instructions, examples and code snippets are available.

supervenn saves you 327 person hours of effort in developing the same functionality from scratch.

It has 787 lines of code, 62 functions and 7 files.

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

Top functions reviewed by kandi - BETA

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

Run theedy algorithm on a matrix
Find the most similar columns of similarities
Compute the column similarity matrix

Get all kandi verified functions for this library.

supervenn Key Features

No Key Features are available at this moment for supervenn.

supervenn Examples and Code Snippets

No Code Snippets are available at this moment for supervenn.

Community Discussions

Trending Discussions on supervenn

Is there an optimal way to find unique elements within N sets with Python?

QUESTION

Is there an optimal way to find unique elements within N sets with Python?

Asked 2021-Apr-27 at 13:16

I'm currently working on an example where I have 45 data frames with around 60,000 strings entries. I would like to know which of the strings are unique when compared to all of the other data frames (or sets) that I have, entry_df['strings'] in the example.

I tried using the library supervenn (https://github.com/gecko984/supervenn) to plot both unique and shared elements within the different sets, but my data is too big to be plotted with this library.

Is there an optimal way to finding these unique elements? I'd like to compare at least 9 groups at once, so that A.intersect B, C, D, E, F, G, H, I = ∅. I thought of iteratively looping over each one of the sets and removing common elements, but I didn't find a way to optimize the memory usage. The code that I've used for plotting the supervenn graph was:

...

ANSWER

Answered 2021-Apr-27 at 13:16

If you need the elements that are placed only once in all the sets, you can use operation ^ for the sets.

set1 ^ set2

returns a set of all elements in either set1 or set2, but not both.

Source https://stackoverflow.com/questions/67283597

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

Vulnerabilities

No vulnerabilities reported

Install supervenn

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