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Diff causes summary

Source: R/diagnostics.R
ks_cause_summary.Rd

Aggregates the note column of cmp$value_diff into a tidy taxonomy: one row per distinct cause, with counts and the columns it affects. Helps answer "what kinds of discrepancies do we have?" before drilling into individual cells.

Usage

ks_cause_summary(x)

Arguments

x

A ks_comparison.

Value

A tibble with columns:

  • cause: short label (e.g. "letter case differs").

  • n_cells: number of cells contributing this cue.

  • n_columns: number of distinct base columns affected.

  • columns: comma-separated sample of the affected columns (capped at 5 names). Sorted by n_cells descending. Zero-row tibble when there are no value differences.

Details

Compound notes (multiple cues joined by "; ") are split into their elementary cues, so a single cell can contribute to several causes. Cells with note = NA (a "plain" value change with no recognised cue) are bucketed as "plain value change".

See also

ks_compare(), ks_row_diff_summary().

Examples

a <- data.frame(id = 1:3, x = c("a", "b ", "c"), y = c(1, 2, 3))
b <- data.frame(id = 1:3, x = c("A", "b",  "c"), y = c(1, 2, 4))
cmp <- ks_compare(a, b, by = "id")
#> ✖ a vs b — 3 value diffs across 2 columns
ks_cause_summary(cmp)
#> # A tibble: 3 × 4
#>   cause                      n_cells n_columns columns
#>   <chr>                        <int>     <int> <chr>  
#> 1 letter case differs              1         1 x      
#> 2 plain value change               1         1 y      
#> 3 whitespace padding on base       1         1 x