Creating Metadata
Auto Detect Metadata
If you don't already have a metadata object, we recommend auto-detecting it based on your data.
detect_from_dataframes
Use this function to automatically detect metadata from your data that you've loaded as a pandas.DataFrame objects.
Parameters:
(required)
data
: Your data, represented as a dictionary. The keys are your table names and values are the pandas.DataFrame objects containing your data.infer_sdtypes
: A boolean describing whether to infer the sdtypes of each column(default)
True
: Infer the sdtypes of each column based on the data.False
: Do not infer the sdtypes. All columns will be marked as unknown, ready for you to manually update.
infer_relationships
: A string describing whether to infer the primary and/or foreign keys.(default)
'primary_and_foreign'
: Infer the primary keys in each table, and the foreign keys in other tables that refer to them'primary_only'
: Infer the primary keys in each table. You can manually add the foreign key relationships later.None
: Do not infer any primary or foreign keys. You can manually add these later.
Output A Metadata object that describes the data
Updating Metadata
The detected metadata is not guaranteed to be accurate or complete. Be sure to carefully inspect the metadata and update information.
For more information about inspecting and updating your metadata, see the Metadata API reference.
Saving, Loading & Sharing Metadata
You can save the metadata object as a JSON file and load it again for future use.
save_to_json
Use this to save the metadata object to a new JSON file that will be compatible with SDV 1.0 and beyond. We recommend you write the metadata to a new file every time you update it.
Parameters
(required)
filepath
: The location of the file that will be created with the JSON metadata
Output (None)
load_from_json
Use this method to load your file as a Metadata object.
Parameters
(required)
filepath
: The name of the file containing the JSON metadata
Output: A Metadata object.
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