Apply a salmon dictionary to a data frame

Renames columns, coerces types, applies factor levels from codes, and reports mismatches. Returns a transformed tibble ready for analysis or packaging.

Usage

apply_salmon_dictionary(df, dict, codes = NULL, strict = TRUE)

Arguments

df

A data frame or tibble to transform

dict

A validated dictionary tibble

codes

Optional tibble with code lists (columns: dataset_id, table_id, column_name, code_value, code_label, etc.)

strict

Logical; if TRUE (default), errors on type coercion failures; if FALSE, warns and coerces to character. A coercion failure is one that R reports with a warning as well as one it reports with an error, so a column typed integer holding "abc" is a failure even though as.integer("abc") only warns and returns NA.

Value

A tibble with renamed columns, coerced types, and factor levels applied

Details

A value that is not in its column's code list has no factor level, so it becomes NA. Each such value is named in a warning, whatever strict is. Blank strings are treated as missing and are not reported. A column backed by a vocabulary skips this codes step: any same-table codes row with a nonblank vocabulary_iri and missing or blank code_value marks the column as vocabulary-backed, even alongside explicit code rows. Independent declared type coercion still applies.

Examples

dict <- infer_dictionary(mtcars)
validate_dictionary(dict)
#> ✔ Dictionary validation passed
applied <- apply_salmon_dictionary(mtcars, dict)
#> ✔ Dictionary validation passed