This project aims to demonstrate the use of Great Expectations for data quality assurance. Great Expectations is a powerful data validation framework that allows you to validate and test your data with minimal code.
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
- Python 3.6 or later
- Great Expectations:
pip install great_expectations
- Clone the repository:
git clone https://github.com/Sparab16/GreatExpectationDemo.git
- Navigate to the project directory:
cd great_expectations_data_quality
- Install the required packages:
pip install -r requirements.txt
The repository contains examples of how to use Great Expectations for data quality assurance. You can find these examples in the great_expectations
directory.
MIT License
Copyright (c) 2022 Shreyas
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.