Metadata are written as a python dictionary. They have to meet following requirements:

• top level dictionary contains category ,tableand features

  • category denotes a group these features belong to for further filtering

  • table is a mandatory entry and it denotes to which feature table features from this notebook will be saved to, learn more in

    Feature table strategy

• features is a dictionary containing key value pairs where key is the name of a feature and value is dictionary containing additional metadata

Supported metadata

• description - Contains description of given feature
• tags - is a list of strings, specifying given feature
• fillna_with - Value that nulls are gonna be replaced with

Example

metadata = {
	"category": "example",
  "table": "table_name"
	"features": {
			"feature1": {
			    "description": "Feature 1",
		 	    "tags": ["tag1", "tag2"],
			    "fillna_with": 0
			},
			"feature2": {
			    "description": "Feature 2",
			    "tags": ["tag1", "tag2"]
			},
	}
}