https://github.com/open-risk/dataqualitytoolkit

Python toolkit for evaluating and visualizing the data quality of excel spreadsheets
https://github.com/open-risk/dataqualitytoolkit

data-quality data-quality-measurement data-science excel spreadsheet

Last synced: 25 days ago
JSON representation

Python toolkit for evaluating and visualizing the data quality of excel spreadsheets

• Host: GitHub
• URL: https://github.com/open-risk/dataqualitytoolkit
• Owner: open-risk
• License: apache-2.0
• Created: 2018-06-21T19:38:27.000Z (almost 7 years ago)
• Default Branch: master
• Last Pushed: 2024-09-05T19:30:14.000Z (8 months ago)
• Last Synced: 2025-03-24T12:21:39.108Z (about 1 month ago)
• Topics: data-quality, data-quality-measurement, data-science, excel, spreadsheet
• Language: Python
• Homepage: https://www.openriskmanagement.com
• Size: 438 KB
• Stars: 8
• Watchers: 1
• Forks: 2
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.rst
  • License: LICENSE.txt

Awesome Lists containing this project

README

        
DataQualityToolkit

==================

A Python toolkit for evaluating and visualizing the data quality of excel spreadsheets, csv files or other tabular data 

![Alt text](DQToolkit.png?raw=true "DQToolkit Visual")

Purpose of the project

======================

DataQualityToolkit is a Python powered library for the evaluation and visualization of the data 

quality of data provided in excel spreadsheets, csv files or other tabular data fetched from the web

General Info

=========================

Author: Open Risk, http://www.openriskmanagement.com

License: Apache 2.0

Documentation: Open Risk Manual, http://www.openriskmanual.org/wiki/Data_Quality

Training: Open Risk Academy, https://www.openriskacademy.com/login/index.php

Development website: https://github.com/open-risk/DataQualityToolkit

Discussion: https://www.openriskcommons.org/

Functionality

=============

NB: The 0.2 release is (still) a heavily (pre-)alpha version. 

You can use DataQualityToolkit to:

- Automatically produce validation reports and visualizations given an existing set of validation rules

- Add to the validation rules

- There is an assumption that the spreadsheets are formatted in standard columnar format with all worksheets starting at the same header row

- There are many assumptions about the structure of wikitables (www source case)

File structure

==============

* datasets/ Contains datasets useful for getting started with the DataQualityToolkit

* examples/ Contains examples

* DQToolkit.py Main objects

Usage

=====

Look at the examples directory on how to produce the visuals include in this README file

Dependencies

============

-  DataQualityToolkit is written in Python and depends on the standard numerical and data processing Python libraries (Numpy, Scipy, Pandas)

-  The Visualization API depends on Matplotlib