Dataset properties

You can use Dataset properties to capture the attributes of a dataset that describe its inherent qualities, features, or characteristics. Properties will be added as a dictionary as you log the dataset or after the dataset has been created.

Properties are optional and work with Dataset.origin, Dataset.clean and Dataset.modeling by assigning to the properties parameter while logging your dataset, as shown in the example below:

origin_resource = FileResource(paths="items.csv")
properties = {"test":10, "QA":"Approved", "Bool":True}
 
# Assigning properties while logging an origin dataset 
origin_dataset = Dataset.origin(
                  name = "Origin_Dataset",
                  resource = origin_resource,
                  properties=properties)

iteration.log(origin_dataset)

You can also update or add dataset properties after a dataset has been logged. You must re-log your dataset to an iteration to save your updated dataset properties.

# Updating or adding properties after logging origin dataset
origin_dataset.properties = {"test":1, "QA":"Not started", "Bool":False}

# Re-log dataset to save updated properties
iteration.log(origin_dataset)