adult_income

A 500-row random sample of the UCI Adult Income dataset, used in
package examples and vignettes.

datasets

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

adult_income function

A tibble with 500 rows and 16 variables:<dl>
<dt>id</dt>
<dd>Row identifier (integer)</dd><dt>age</dt>
<dd>Age in years (integer)</dd><dt>workclass</dt>
<dd>Employment type (character)</dd><dt>fnlwgt</dt>
<dd>Final weight, a census sampling weight (integer)</dd><dt>education</dt>
<dd>Highest level of education (character)</dd><dt>education_num</dt>
<dd>Education encoded as an integer (integer)</dd><dt>marital_status</dt>
<dd>Marital status (character)</dd><dt>occupation</dt>
<dd>Occupation category (character)</dd><dt>relationship</dt>
<dd>Relationship to householder (character)</dd><dt>race</dt>
<dd>Race (character)</dd><dt>sex</dt>
<dd>Sex (character)</dd><dt>capital_gain</dt>
<dd>Capital gains (integer)</dd><dt>capital_loss</dt>
<dd>Capital losses (integer)</dd><dt>hours_per_week</dt>
<dd>Hours worked per week (integer)</dd><dt>native_country</dt>
<dd>Country of origin (character)</dd><dt>income</dt>
<dd>Income bracket: <code>&lt;=50K</code> or <code>&gt;50K</code> (character)</dd>
</dl>

Format

Adult Income dataset (500-row sample) — adult_income

A tibble with 500 rows and 16 variables:<dl>
<dt>id</dt>
<dd>Row identifier (integer)</dd>

<dt>age</dt>
<dd>Age in years (integer)</dd>

<dt>workclass</dt>
<dd>Employment type (character)</dd>

<dt>fnlwgt</dt>
<dd>Final weight, a census sampling weight (integer)</dd>

<dt>education</dt>
<dd>Highest level of education (character)</dd>

<dt>education_num</dt>
<dd>Education encoded as an integer (integer)</dd>

<dt>marital_status</dt>
<dd>Marital status (character)</dd>

<dt>occupation</dt>
<dd>Occupation category (character)</dd>

<dt>relationship</dt>
<dd>Relationship to householder (character)</dd>

<dt>race</dt>
<dd>Race (character)</dd>

<dt>sex</dt>
<dd>Sex (character)</dd>

<dt>capital_gain</dt>
<dd>Capital gains (integer)</dd>

<dt>capital_loss</dt>
<dd>Capital losses (integer)</dd>

<dt>hours_per_week</dt>
<dd>Hours worked per week (integer)</dd>

<dt>native_country</dt>
<dd>Country of origin (character)</dd>

<dt>income</dt>
<dd>Income bracket: <code>&lt;=50K</code> or <code>&gt;50K</code> (character)</dd>


</dl>

adult_income: Adult Income dataset (500-row sample)

Description

Usage

Arguments

Format