metasyn.MetaFrame

class metasyn.MetaFrame(meta_vars, n_rows, file_format=None, name='single_table')

Container for statistical metadata describing a dataset.

This class is used to fit a MetaFrame to a Polars DataFrame, serialize and save the MetaFrame to a file, read a MetaFrame from a file, and create a synthetic Polars DataFrame.

A MetaFrame represents a metadata frame, which is a structure that holds statistical metadata about a dataset. The data contained in a MetaFrame follows the Generative Metadata Format (GMF). The metadata is contained in a collection of MetaVar objects, with each MetaVar representing a column (variable).

A MetaFrame can easily be created using the fit_dataframe method, which takes a Polars DataFrame and fits a MetaFrame to it.

Parameters:

• meta_vars (List[MetaVar]) – List of variables representing columns in a DataFrame.

• n_rows (int) – Number of rows in the original DataFrame.

• privacy_package – Package that supplies the distributions.

• file_format (Union[None, BaseFileInterface, dict[str, Any]])

• name (str)

__init__(meta_vars, n_rows, file_format=None, name='single_table')

Parameters:

• meta_vars (List[MetaVar])

• n_rows (int)

• file_format (None | BaseFileInterface | dict[str, Any])

• name (str)

Methods

__init__(meta_vars, n_rows[, file_format, name])
fit_dataframe(df[, var_specs, plugins, ...])	Create a metasyn object from a polars (or pandas) dataframe.
from_config(meta_config)	Create a MetaFrame using a configuration, but without a DataFrame.
from_dict(gmf_dict[, table_name])
load(fp[, validate, table_name])	Read a MetaFrame from a JSON or TOML GMF file.
load_json(fp[, validate, table_name])	Read a MetaFrame from a JSON file.
save(fp[, validate])	Serialize and save the MetaFrame to a JSON or TOML file, following the GMF format.
save_json(fp[, validate])	Serialize and save the MetaFrame to a JSON file, following the GMF format.
synthesize([n, seed, progress_bar, ...])	Create a synthetic Polars dataframe.
to_dict()	Create dictionary with the properties for recreation.
write_synthetic([file_name, n, seed, ...])	Write a synthetic dataset to a file.

Attributes

descriptions	Return the descriptions of the columns.
file_format
n_columns	Number of columns of the original dataframe.