R: Automated Data Quality Checks for Recurring Dataset Deliveries

# Automated Data Quality Checks for Recurring Dataset Deliveries

## Documentation for package ‘dqcheckr’ version 0.2.1

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

check_allowed_values | QC-09: Check for values outside the allowed set
check_col_count | QC-05: Report column count
check_distinct_counts | QC-08: Report distinct value counts for character columns
check_duplicate_rows | QC-03: Check for fully-duplicate rows
check_empty_column | QC-02: Check for entirely empty columns
check_inferred_types | QC-06: Report inferred column types
check_key_uniqueness | QC-12: Check uniqueness of key column(s)
check_min_row_count | QC-14: Check row count bounds and optional file size
check_missing_rate | QC-01: Check missing rate per column
check_non_numeric | QC-11: Check non-numeric rate in numeric columns
check_numeric_bounds | QC-10: Check for out-of-range numeric values
check_numeric_stats | QC-07: Report numeric summary statistics
check_outliers | QC-15: Detect statistical outliers in numeric columns
check_pattern | QC-13: Check values against a regex pattern
check_row_count | QC-04: Report row count
check_schema_contract | SC-01 / SC-02: Check columns against the expected schema contract
compare_snapshots | Compare two snapshots from the SQLite database
detect_files | Detect current and previous dataset files
dq_result | Construct a data quality result object
infer_col_type | Infer the logical type of a character column
list_snapshots | List snapshots available in the database
load_config | Load and merge dataset configuration
overall_status | Compute the worst status across a list of dq_result objects
read_dataset | Read a dataset file into a data frame
read_recent_snapshots | Read recent snapshot history from the SQLite database
resolve_col_type | Resolve the effective type of a column, respecting config overrides
run_comparison_checks | Run all version comparison checks between two dataset snapshots
run_custom_checks | Run organisation-specific custom checks
run_dq_check | Run a full data quality check pipeline
run_qc_checks | Run all generic quality checks on a dataset