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sdv.SDV

class sdv.SDV(model=None, model_kwargs=None)

Automated generative modeling and sampling tool.

Allows the users to generate synthetic data after creating generative models for their data.

Parameters

• model (type) – Class of the model to use. Defaults to sdv.relational.HMA1.

• model_kwargs (dict) – Keyword arguments to pass to the model. If no model is given, this defaults to using a GaussianCopula with gaussian distribution and FrequencyEncoder_noised categorical transformer.

__init__(model=None, model_kwargs=None)

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__([model, model_kwargs])	Initialize self.
fit(metadata[, tables, root_path])	Fit this SDV instance to the dataset data.
load(path)	Load a SDV instance from a given path.
sample([table_name, num_rows, …])	Generate synthetic data for one table or the entire dataset.
sample_all([num_rows, reset_primary_keys])	Sample the entire dataset.
save(path)	Save this SDV instance to the given path using cloudpickle.

Attributes

DEFAULT_MODEL_KWARGS

sdv sdv.SDV.fit