SAS-style PROC FORMAT for R: create and apply value formats, range-based formatting, reverse formatting (invalue), and consistent handling of missing values (NA, NULL, NaN).

Repository: github.com/crow16384/ksformat — source code, issue tracker, and development.

Installation

From GitHub (after cloning or from your repo URL):

# install.packages("remotes")
remotes::install_github("crow16384/ksformat")

From local source:

install.packages(".", repos = NULL, type = "source")
# or
devtools::install()

Features

• Format creation — Value-to-label mappings like SAS PROC FORMAT
• Format application — Apply formats to vectors and data frames
• Reverse formatting — Convert labels back to values (INVALUE)
• Missing value handling — NA, NULL, NaN, and empty values
• Range support — Numeric ranges with inclusive/exclusive bounds
• Multilabel — A single value can match multiple labels (fput_all)
• Expression labels — Dynamic labels with .x1, .x2, … evaluated at apply-time
• Case-insensitive matching — ignore_case = TRUE in fnew
• Numeric patterns — %f-style continuous formatting with grouping, prefix/suffix text, and currency-style output
• Date/time/datetime — Built-in SAS format names and custom strftime patterns
• Import/export — Parse SAS-like text (fparse), export (fexport), import CNTLOUT CSV (fimport)
• Format library — Register and retrieve formats globally

Quick start

Discrete formatting

library(ksformat)
fnew(
  "M" = "Male",
  "F" = "Female",
  .missing = "Unknown",
  name = "sex"
)
fput(c("M", "F", NA, "X"), "sex")
# [1] "Male"    "Female"  "Unknown" "X"

Numeric ranges

fparse(text = '
VALUE age (numeric)
  [0, 18)   = "Child"
  [18, 65)  = "Adult"
  [65, HIGH] = "Senior"
  .missing   = "Age Unknown"
;
')
fputn(c(5, 25, 70, NA), "age")
# [1] "Child"       "Adult"       "Senior"      "Age Unknown"

Reverse formatting (invalue)

finput("Male" = 1, "Female" = 2, name = "sex_inv")
finputn(c("Male", "Female", "Unknown"), "sex_inv")
# [1]  1  2 NA

Format library

fprint()              # list all registered formats
fmt <- format_get("sex")
fclear("sex")         # remove one format
fclear()              # clear all

Interactive library browser (Shiny)

if (interactive() && requireNamespace("shiny", quietly = TRUE)) {
  format_library_app()
}

The app shows both VALUE (ks_format) and INVALUE (ks_invalue) objects, supports name/type filtering, shows a formatted mapping table, and includes library management actions (remove selected, clear all, or quit).

In RStudio, you can also open it from Addins as Format Library Browser.

Data frames

df <- data.frame(
  sex = c("M", "F", "M", NA),
  age = c(15, 25, 70, 35)
)
fput_df(df, sex = format_get("sex"), age = format_get("age"), suffix = "_label")

Multilabel formats

With multilabel = TRUE, a single value can match multiple labels. Use fput_all() to collect all matches:

fnew(
  "0,17,TRUE,TRUE"  = "Pediatric",
  "18,Inf,TRUE,TRUE" = "Adult",
  "3,5,TRUE,TRUE"   = "Serious",
  name = "ae_age", type = "numeric", multilabel = TRUE
)
fput_all(c(10, 25, 4), "ae_age")
# [[1]] "Pediatric"
# [[2]] "Adult"
# [[3]] "Pediatric" "Serious"

Date/time/datetime formats

SAS date format names are auto-resolved — no pre-creation needed:

fputn(Sys.Date(), "DATE9.")
# [1] "25MAR2026"
fputn(Sys.Date(), "MMDDYY10.")
# [1] "03/25/2026"
# Custom strftime pattern
fnew_date("%d.%m.%Y", name = "ru_date", type = "date")
fput(Sys.Date(), "ru_date")
# [1] "25.03.2026"

Time (seconds since midnight) and datetime are also supported:

fputn(3600, "TIME8.")
# [1] "1:00:00"
fputn(Sys.time(), "DATETIME20.")

Expression labels

Labels containing .x1, .x2, etc. are evaluated as R expressions at apply-time. Pass extra arguments through fput(x, fmt, ...):

stat_fmt <- fnew(
  "n"   = "sprintf('%s', .x1)",
  "pct" = "sprintf('%.1f%%', .x1 * 100)",
  name = "stat", type = "character"
)
fput(c("n", "pct"), stat_fmt, c(42, 0.053))
# [1] "42"   "5.3%"

Use e() to mark a label for evaluation even without .xN placeholders:

fnew("ts" = e("format(Sys.time(), '%Y-%m-%d')"), name = "demo")
fput("ts", "demo")

Case-insensitive matching

fnew("M" = "Male", "F" = "Female", name = "sex_nc",
     type = "character", ignore_case = TRUE)
fput(c("m", "F", "M", "f"), "sex_nc")
# [1] "Male"   "Female" "Male"   "Female"

Missing value handling

Priority order:

1. NA, NULL, NaN → .missing label if defined, otherwise NA
2. Exact match → value–label mapping
3. Range match → range label (numeric formats)
4. No match → .other label or original value

Options: keep_na = TRUE, na_if, include_empty = TRUE.

Cheat sheet

• In R: run ksformat_cheatsheet() to open the cheat sheet in your browser (HTML), or ksformat_cheatsheet("pdf") for the PDF.
• In this repo: HTML | PDF

Function reference

Development

install.packages(c("roxygen2", "testthat", "devtools"))
devtools::document()
devtools::test()
devtools::check()

When bumping the package version, update DESCRIPTION and then run
Rscript scripts/sync-version.R to refresh version references in cran-comments.md and any other synced files.

License

GPL-3. See https://www.gnu.org/licenses/gpl-3.0.html.