We're looking to modernize data validation by contributing to the Great Expectations Library as part of their hackathon.
Expectations for various entities in the world.
Courtesy of @mmi333
Providing a set of expectations using the geos (pygeos->shapely) library to calculate various relationships between points and reference shapes (and geocoded shapes).
Great Expectations contributions
In healthcare data, a disease can be coded as an ICD-10 category or subcategory (more specific). This expectation determines whether column matches either ICD-10 category or subcategory.
A ColumnMapExpectation for validating medicine properties (name, color, and shape)
Two expectations for geohashes: if they are valid and if they correspond with latlng coordinates they're associated with.
I've done the HTTP method suggestion. Maybe more on the way!
I've created two new expectations:
- An expectation to validate timezones (e.g. America/New_York)
- An expectation to validate currency codes (e.g. USD, EUR, GBP)
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