Creates Assertion Tests
Assert Date Value in Column
Check if the fieldnames of the dataset are the same
Assert Field Uniqueness Consistency Between Data and Metadata
Assert Field Existence in New Data
Assert Logical Value in Column
Assert Consistency of Missing Values in Data
Assert No Duplicates in Group
Assert Range Validation for Data Fields
Assert Type Consistency Between Data and Metadata
Assert Message Based on Type
Calculate the percentage of categories in a data vector
check double columns
Check for Duplicate Rows in Selected Columns
Check for columns with only NA values
Check for No Duplicate Rows
Check for No Duplicates in Group
Check for Non-Zero Rows
Check for Numeric or Integer Type
Check for POSIXct Type
Check rows
Check for Columns with Only 0s
Count more than 1
Create categorical details csv
Create data types tibble
Create dataset summary statistics table
Create field info
Create numeric details csv
Create subset fields
Drop NA column names
Duplicates in column
Find Common Columns Between Data Frames
Find the maximum numeric value in a vector, ignoring non-numeric value...
Find the minimum numeric value in a vector, ignoring non-numeric value...
Find pattern in R scripts
Compute distribution statistics for a numeric vector
Retrieve the class of the first element of a vector
Get values of column
Identify Possible Join Pairs Between Data Frames
Identify Outliers in a Data Frame Column
Check if a column in a dataframe has unique values
MD complete cases
Construct Regex for Matching Function Parameter Content
Generate regular expression of a time.
Generate regular expression of a year date.
Remove Duplicates and NA Values from Input
retrieve_function_calls
Retrieve functions and packages
Retrieve packages that are loaded in a script
retrieve_sourced_scripts
retrieve_string_assignments
Return Assertion Messages
Read and return the mtcars testfile
Run All Data Validation Assertions
Detect string in file
Test all equal
unique id
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.