metadata

Create a metadata object describing a dataset's column types

Generates synthetic tabular data from real datasets using
Gaussian copula models, with parametric marginal selection for
numerical columns and a cumulative-frequency embedding that brings
categorical and boolean columns into the same joint copula. Includes
a metadata system with column types and primary keys, declarative
constraints enforced via rejection sampling, conditional sampling,
and quality, validity and privacy reports modeled on those of the
'SDMetrics' library. Inspired by the Python 'SDV' (Synthetic Data
Vault) library by 'DataCebo'; see Patki, Wedge and Veeramachaneni
(2016) "The Synthetic Data Vault" <doi:10.1109/DSAA.2016.49>.

Kailas Venkitasubramanian

rsdv

Synthetic Tabular Data Generation with Gaussian Copulas

metadata function

<dl><dt>data</dt>
<dd>Optional data frame. If supplied, column types are
auto-detected. You can override them with <code>set_column_type()</code>.</dd></dl>

Arguments

Create a metadata object describing a dataset's column types — metadata

<dl>

<dt>data</dt>
<dd>Optional data frame. If supplied, column types are
auto-detected. You can override them with <code>set_column_type()</code>.</dd>

</dl>

metadata: Create a metadata object describing a dataset's column types

Description

Usage

Value

Arguments

Examples