Data Checker for Validating Data Frames Against Defined Schema

Documentation for package ‘data.checker’ version 2.0.0

Help Pages

add_check	Add a custom check to the validator
add_check_custom	Add a custom check to the validator
add_qa_entry	Add a QA Entry to the validator's QA Log
check	Validate a Validator Object
check_and_export	Validate data against a schema and output results
check_backseries	Check backseries consistency
check_colnames	Check Column Names against schema
check_column_contents	Check Column Contents against schema and checks
check_completeness	Check dataset for missing columns
check_duplicates	Check for duplicate rows. Can use subset of columns to check for duplicates if 'duplicates_cols' is specified in the schema. Otherwise, all columns are used for duplicate check.
check_schema_contents_against_df	Check schema contents against the data frame provided
check_types	Check Column Types and Classes
export	Generic export function
export.Validator	Export Validator Log
hard_checks_status	Check the status of errors and warnings in the validator log
iqr_bounds	Flag outliers based on Interquartile Range (IQR). Outliers are flagged if they are below Q1 - (mulitplier * IQR) or above Q3 + (multiplier * IQR).
is_column_contents_valid	Check column contents valid
is_type_valid	Check type of column in schema is valid
is_valid_column_values	Check that max values are not less than min values in column schema
is_valid_schema	Check if the schema is valid
log_html	Generate HTML Representation of a Log
log_pointblank_outcomes	Log pointblank validation outcomes to a validator log
log_to_table	Convert Validator Log to Table
new_validator	Validator Constructor
print.Validator	Print Validator Log
run_checks	Run column checks
types_to_classes	Convert complex types to the correct types and classes
validate_and_convert_date_formats	Validate date formats in the schema This function checks that any date formats specified in the schema are valid and can be parsed correctly.
z_score	Check Z Score of Numeric Columns