Read CV data from an Excel workbook

Reads all sheets from a curriculr-formatted Excel workbook and returns them as a named list of data frames. Each sheet becomes one list element, named after the sheet. The profile sheet is returned as a named character vector for convenient scalar access. The theme sheet is returned as a named character vector keyed by the key column. The sections sheet is returned as a data frame in the order the rows appear in the workbook — row order controls section render order and must not be sorted.

Usage

read_cv_data(path = "data/cv-data.xlsx", variant = "cv")

Arguments

path

A character string. Path to the Excel workbook. Defaults to "data/cv-data.xlsx".

variant

A character string. Controls which rows are included from each section sheet. "cv" (the default) returns all rows. "resume" returns only rows where include_in_resume is TRUE. Sections that lack an include_in_resume column are included in full regardless of variant.

Value

A named list with one element per sheet in the workbook. The profile element is a named character vector; the theme element is a named character vector (or NULL if the theme sheet is absent); all other elements are data frames. The include_in_resume column is dropped from returned data frames — it is used for filtering only and is not passed to the rendering pipeline. Access sections as cv$education, cv$experience, etc. Access profile fields as cv$profile[["first_name"]]. Access theme values as cv$theme[["accent_color"]]. Access the sections control sheet as cv$sections.

Details

Sheets containing a startYear column are sorted in descending order by startYear so that the most recent entries appear first. The profile, theme, and sections sheets are exempt from sorting.

The workbook must follow the curriculr schema. Every section sheet should contain a title column as the primary entry label. The profile sheet must contain field and value columns. The sections sheet must contain at minimum section and label columns. The theme sheet, if present, must contain key and value columns.

All cell values are read as character strings after import. Numeric columns such as startYear and endYear are coerced to character so that downstream rendering treats them uniformly. The include_in_resume column is read as a logical before coercion and used for row filtering when variant = "resume".

Empty cells and cells containing the literal string "NA" are both converted to NA.

If the theme sheet is absent, cv$theme is NULL and create_cv() will fall back to built-in defaults.

Examples

# \donttest{
# Read the sample data shipped with the package
cv <- read_cv_data(
  system.file("extdata", "cv-data-template.xlsx", package = "curriculr")
)
cv$education
#>                                  title startYear endYear
#> 1 Summer Intensive, Figurative Drawing      1993    1993
#> 2  Bachelor of Fine Arts, Illustration      1990    1994
#>                                  institution          where
#> 1 Skowhegan School of Painting and Sculpture    Madison, ME
#> 2              Rhode Island School of Design Providence, RI
#>                                                                                           detail
#> 1                        Competitive residency program. Studied under noted figurative painters.
#> 2 Concentration in editorial and narrative illustration. Senior thesis exhibited at RISD Museum.
cv$profile[["first_name"]]
#> [1] "Frank"
# }

if (FALSE) { # \dontrun{
# Read a user-supplied file
cv <- read_cv_data("~/my_cv/cv-data.xlsx")

# Resume variant
cv <- read_cv_data("~/my_cv/cv-data.xlsx", variant = "resume")
} # }