pyspc | Statistical Process Control Charts Library for Humans | Analytics library

by carlosqsilva Python Version: 0.4 License: GPL-3.0

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

kandi X-RAY | pyspc Summary

pyspc is a Python library typically used in Analytics applications. pyspc has no bugs, it has no vulnerabilities, it has build file available, it has a Strong Copyleft License and it has low support. You can install using 'pip install pyspc' or download it from GitHub, PyPI.

Statistical Process Control Charts Library for Humans. PySpc is a Python library aimed to make Statistical Process Control Charts as easy as possible. Take a look at my other project cchart-online.

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Quality

Security

License

Reuse

Support

pyspc has a low active ecosystem.

It has 150 star(s) with 61 fork(s). There are 17 watchers for this library.

It had no major release in the last 12 months.

There are 5 open issues and 1 have been closed. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of pyspc is 0.4

Quality

pyspc has 0 bugs and 0 code smells.

Security

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

pyspc code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

pyspc is licensed under the GPL-3.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

Reuse

pyspc 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.

Installation instructions are not available. Examples and code snippets are available.

pyspc saves you 482 person hours of effort in developing the same functionality from scratch.

It has 1135 lines of code, 74 functions and 27 files.

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

Top functions reviewed by kandi - BETA

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

Function called when save button clicked
Return a list of subplots
Save the plot
Make the plot
Plot the covariance matrix
Compute the covariance matrix
Compute covariance matrix
Called when the plot is pressed
Redraw the figure
Confirm file selection
Display a text message
Plot a list of points on one side
Test whether the data points lie within the given center
Open file dialog
Add a treeview
Called when the clipboard is clicked
Called when the plot button is clicked
Open the data table
Plot rrule1 and lcl
Prompts the user to confirm dialog

Get all kandi verified functions for this library.

pyspc Key Features

No Key Features are available at this moment for pyspc.

pyspc Examples and Code Snippets

AssertionError when using self-defined nested list in Pyspc

Python

Lines of Code : 2

License : Strong Copyleft (CC BY-SA 4.0)

Copy

abc=[[2,3,4],[4,5,6],[1,4,5],[3,4,4],[4,5,6]]

Community Discussions

Trending Discussions on pyspc

AssertionError when using self-defined nested list in Pyspc

QUESTION

AssertionError when using self-defined nested list in Pyspc

Asked 2017-Aug-26 at 11:09

I installed pyspc and run on Jupyter Notebook successfully when using original samples. But when I tried introducing a self defined nested list and an error message showed up. pyspc library: https://github.com/carlosqsilva/pyspc

...

ANSWER

Answered 2017-Aug-26 at 11:09

Check the data you have accidentally used the . instead of , for value [4,5.6], second element of the list.

Here is the corrected data

Source https://stackoverflow.com/questions/45892416

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

Vulnerabilities

No vulnerabilities reported

Install pyspc

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