numpy-groupies | Optimised tools for group-indexing operations | Computer Vision library

by ml31415 Python Version: 0.11.1 License: BSD-2-Clause

X-Ray Key Features Code Snippets(2)Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | numpy-groupies Summary

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

Optimised tools for group-indexing operations: aggregated sum and more

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Security

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numpy-groupies has a low active ecosystem.

It has 172 star(s) with 20 fork(s). There are 10 watchers for this library.

There were 2 major release(s) in the last 12 months.

There are 8 open issues and 46 have been closed. On average issues are closed in 185 days. There are 2 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of numpy-groupies is 0.11.1

Quality

numpy-groupies has 0 bugs and 0 code smells.

Security

numpy-groupies has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

numpy-groupies code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

numpy-groupies 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

numpy-groupies 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.

numpy-groupies saves you 1630 person hours of effort in developing the same functionality from scratch.

It has 3619 lines of code, 224 functions and 20 files.

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

Top functions reviewed by kandi - BETA

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

Return a dict containing the main command class
Extract version information
Get the project root directory
Construct a ConfigParser from root
Create the versioneer config file
Install versioneer
Extract the version information from the VCS
Calculate the concatenation op
Generic aggregation function
Return the function object corresponding to the given function
Benchmark functions
Scans the setup py file
Create a function that loops over the function
Get alias dictionary
Wrapper function for aggregation function
Relabels all groups
Return a dictionary of functions
Returns a dictionary of cfuncs
Generic callable function
Return the minimum value of an array
Return the maximum value of the argmax
Compute the product of a group
Removes build folders
Return the last value of an array with the same shape
Aggregate a group
Compute the first element of the array

Get all kandi verified functions for this library.

numpy-groupies Key Features

No Key Features are available at this moment for numpy-groupies.

numpy-groupies Examples and Code Snippets

Python numpy groupby multiple columns

Python

Lines of Code : 58

License : Strong Copyleft (CC BY-SA 4.0)

Copy

group_idx = df.iloc[:,:3].values
a = df.iloc[:,-1].values

s = group_idx.max(0)+1
lidx = np.ravel_multi_index(group_idx.T,s)

sidx, unq_lidx = pd.factorize(lidx)
pp = np.empty(len(unq_lidx), dtype=int)
pp[sidx] = np.arange(len(sidx))
k1 =

numpy: Compressing block matrix

Python

Lines of Code : 36

License : Strong Copyleft (CC BY-SA 4.0)

Copy

>>> M1 = np.arange(25).reshape((5,5))
>>> M1
array([[ 0,  1,  2,  3,  4],
       [ 5,  6,  7,  8,  9],
       [10, 11, 12, 13, 14],
       [15, 16, 17, 18, 19],
       [20, 21, 22, 23, 24]])

>&

Community Discussions

Trending Discussions on numpy-groupies

Python numpy groupby multiple columns

QUESTION

Python numpy groupby multiple columns

Asked 2020-Nov-01 at 20:04

Is there a way to make a group by aggregation by multiple columns in numpy? Im trying to do it with this module: https://github.com/ml31415/numpy-groupies Goal is to get a faster groupby than pandas. for example:

...

ANSWER

Answered 2020-Oct-30 at 10:08

Given that group_idx has positive values, we can use a dimensionality-reduction based method. We are assuming the first three columns as the groupby ones and the last (fourth) one as the data column to be summed.

Approach #1

We will stick to NumPy tools and also bring in pandas.factorize in the mix.

Source https://stackoverflow.com/questions/64533781

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

Vulnerabilities

No vulnerabilities reported

Install numpy-groupies

If you have pip, then simply:. Note that numpy_groupies doesn't have any compulsory dependencies (even numpy is optional) so you should be able to install it fairly easily even without a package manager. If you just want one particular implementation of aggregate (e.g. aggregate_numpy.py), you can download that one file, and copy-paste the contents of utils.py into the top of that file (replacing the from .utils import (...) line).

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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