Skip to contents

Audit a Vector Transformation

Source: R/audit-transform.R
audit_transform.Rd

Applies a transformation function to a vector and reports what changed. Works with any vector type: character, numeric, Date/POSIXct, factor, or logical. Diagnostics are adapted to the detected input type.

Usage

audit_transform(
  x,
  clean_fn,
  name = NULL,
  .tolerance = sqrt(.Machine$double.eps)
)

# S3 method for class 'audit_transform'
print(x, ...)

Arguments

x

Vector to transform. Accepted types: character, numeric, Date, POSIXct, factor, or logical.

clean_fn

A function applied to x that returns a vector of the same length, or a pre-computed vector of the same length (used directly as the transformation result).

name

Optional name for the variable (used in output). If NULL, captures the variable name from the call.

.tolerance

Numeric tolerance used for the "changed beyond tolerance" diagnostic (numeric type only). Defaults to sqrt(.Machine$double.eps).

...

Additional arguments (currently unused).

Value

An S3 object of class audit_transform containing:

name

Name of the variable

clean_fn_name

Name of the transformation function, or "<pre-computed>" when a vector was supplied directly

type_class

Detected type: "character", "numeric", "Date", "POSIXct", "factor", or "logical"

n_total

Total number of elements

n_changed

Count of values that changed (including NA status changes)

n_unchanged

Count of values that stayed the same

n_na_before

Count of NA values before transformation

n_na_after

Count of NA values after transformation

pct_changed

Percentage of total elements that changed

change_examples

Data frame with before/after pairs (up to 10)

diagnostics

Type-specific diagnostic list, or NULL for character

cleaned

The transformed vector, retaining its type

See also

diagnose_strings()

Other data quality: diagnose_nas(), diagnose_strings(), get_summary_table(), summarize_column(), tab()

Examples

# Character
x <- c("  hello ", "WORLD", "  foo  ", NA)
result <- audit_transform(x, trimws)
result$cleaned
#> [1] "hello" "WORLD" "foo"   NA     

# Numeric
prices <- c(10.5, 20.0, NA, 30.0)
audit_transform(prices, function(v) round(v))
#> 
#> ── Transformation Audit [numeric]: prices ──────────────────────────────────────
#> Function: function(v) round(v)
#> 
#>   Metric                       Value
#>   ──────────────  ──────────────────
#>   Total elements                   4
#>   NA (before)                      1
#>   NA (after)                       1
#>   Changed         1 (25.0% of total)
#>   Unchanged                        3
#> 
#> Numeric summary:
#>   Metric  Before  After
#>   ──────  ──────  ─────
#>   Mean     20.17     20
#>   SD       9.751     10
#>   Min       10.5     10
#>   Median      20     20
#>   Max         30     30
#>   NaN          0      0
#>   Inf          0      0
#> 
#> Mean absolute delta: 0.5
#> Changed beyond tolerance: 1 (33.3%)
#> 
#> Examples of changes (showing 1 of 1):
#>  before after
#>    10.5    10
#> 
#> Access cleaned vector with: `result$cleaned`

# Pre-computed result
audit_transform(prices, round(prices))
#> 
#> ── Transformation Audit [numeric]: prices ──────────────────────────────────────
#> Function: <pre-computed>
#> 
#>   Metric                       Value
#>   ──────────────  ──────────────────
#>   Total elements                   4
#>   NA (before)                      1
#>   NA (after)                       1
#>   Changed         1 (25.0% of total)
#>   Unchanged                        3
#> 
#> Numeric summary:
#>   Metric  Before  After
#>   ──────  ──────  ─────
#>   Mean     20.17     20
#>   SD       9.751     10
#>   Min       10.5     10
#>   Median      20     20
#>   Max         30     30
#>   NaN          0      0
#>   Inf          0      0
#> 
#> Mean absolute delta: 0.5
#> Changed beyond tolerance: 1 (33.3%)
#> 
#> Examples of changes (showing 1 of 1):
#>  before after
#>    10.5    10
#> 
#> Access cleaned vector with: `result$cleaned`