It provides a DataTable object, which contains the physical, logical, and semantic data types. It can be used with Featuretools, EvalML, and general machine learning applications where logical and semantic typing information is important.
Woodwork provides simple interfaces for adding and updating logical and semantic typing information, as well as selecting data columns based on the types.
Below is an example of using a Woodwork DataTable to automatically infer the Logical Types for a data structure and select columns with specific types.
import woodwork as ww
data = ww.demo.load_retail(nrows=100, return_dataframe=True)
dt = ww.DataTable(data, name="retail")
filtered_dt = dt.select(include=['numeric', 'Boolean'])