assert_missing_values

This function checks whether the percentage of missing values in a dataset matches the documented percentage
in a metadata reference. It warns if there are significant discrepancies.

Offers a comprehensive set of assertion tests to help users validate the integrity of their data.
These tests can be used to check for specific conditions or properties within a dataset and
help ensure that data is accurate and reliable.
The package is designed to make it easy to add quality control checks to data analysis
workflows and to aid in identifying and correcting any errors or inconsistencies in data.

Tomer Iwan

vvauditor

Creates Assertion Tests

Hajo Bons

assert_missing_values function

<dl><dt>data</dt>
<dd>A data frame. The dataset to check for missing values.</dd>
<dt>metadata</dt>
<dd>A data frame. Metadata containing expected missing value percentages and valid value counts.
It must include the columns <code>raw_field_name</code>, <code>percentage_of_missing_values</code>, <code>count_of_valid_values</code>,
and <code>preferred_field_name</code>.</dd></dl>

Arguments

Assert Consistency of Missing Values in Data — assert_missing_values

<dl>

<dt>data</dt>
<dd>A data frame. The dataset to check for missing values.</dd>


<dt>metadata</dt>
<dd>A data frame. Metadata containing expected missing value percentages and valid value counts.
It must include the columns <code>raw_field_name</code>, <code>percentage_of_missing_values</code>, <code>count_of_valid_values</code>,
and <code>preferred_field_name</code>.</dd>

</dl>

assert_missing_values: Assert Consistency of Missing Values in Data

Description

Usage

Value

Arguments