How to install Great Expectations locally
note Great Expectations is developed and tested on macOS and Linux Ubuntu. Installation for Windows users may vary from the steps listed below. If you have questions, feel free to reach out to the …
Toggle analytics events - Great Expectations
Toggle analytics events To help us improve Great Expectations, we track analytics events by default. The data includes things like which GX features are used with what OS and Python version. While …
Set up a GX environment - Great Expectations
Learn how to set up a Python environment for GX, install the GX library, and get a Data Context for project management from a Python script, IDE, or interpreter.
Install Great Expectations with Data Source dependencies
Note Great Expectations is developed and tested on macOS and Linux Ubuntu. The installation on Windows may differ from the following procedure. If you have questions or encounter issues, post …
Create a Data Context - Great Expectations
A Data Context defines the storage location for metadata, such as your configurations for Data Sources, Expectation Suites, Checkpoints, and Data Docs. It also contains your Validation Results and the …
Compatibility reference - Great Expectations
Compatibility reference The following table defines integrations and tools supported by GX Cloud and GX Core.
Connect to Filesystem data - Great Expectations
Connect to data stored as files in a folder hierarchy and organize that data into Batches for retrieval and validation.
Changelog - Great Expectations
This is documentation for Great Expectations 0.15.50, which is no longer actively maintained.
Validate data distribution with GX | Great Expectations
Validate data distribution with GX Data distribution analysis is a critical aspect of data quality management, focusing on understanding the spread, shape, and characteristics of data within a …