Creating Metadata
This guide will walk you through creating the metadata using the Python API.
Auto Detect Metadata
Once you have loaded your data into Python, you can auto-detect your actual data.
detect_from_dataframe
Use this function to automatically detect metadata from your data that you've loaded as a pandas.DataFrame object.
Parameters:
(required)
data
: Your pandas DataFrame object that contains the datatable_name
: A string describing the name of your table. SDV will use the table name when referring to your table in the metadata, as well as any warnings or descriptive error messages.(default) By default, we'll name your data table
'table'
Output A Metadata object that descibes the data
Updating Metadata
The detected metadata is not guaranteed to be accurate or complete. Be sure to carefully inspect the metadata and update it so it accurately represents your data.
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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