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`dunlin`: Tools for Clinical Trial Data Wrangling

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dunlin provides a variety of data tools to reformat and manipulate a subset of the tables in a data set.

Installation

install.packages("dunlin", repos = c("https://insightsengineering.r-universe.dev", getOption("repos")))

# install.packages("pak")
pak::pak("insightsengineering/dunlin@*release")

Alternatively, you might also use the development version.

install.packages("dunlin", repos = c("https://pharmaverse.r-universe.dev", getOption("repos")))

# install.packages("pak")
pak::pak("insightsengineering/dunlin")

Usage

library(dunlin)

df1 <- data.frame(
  "id" = c("a", "b", NA, "a", "k", "x"),
  "id2" = factor(c("f1", "f2", NA, NA, "f1", "f1")),
  "val" = letters[1:6]
)
df2 <- data.frame(
  "id" = c("a", "b", NA, "a", "k", "x"),
  "id2" = factor(c("f1", "f2", NA, NA, "f1", "f1")),
  "num" = 1:6
)

db <- list(df1 = df1, df2 = df2)

prop_db <- propagate(db, "df1", "val", c("id", "id2"))

which returns prop_db as

 $df1
    id  id2 val
1    a   f1   a
2    b   f2   b
3 <NA> <NA>   c
4    a <NA>   d
5    k   f1   e
6    x   f1   f

$df2
    id  id2 num val
1    a   f1   1   a
2    b   f2   2   b
3 <NA> <NA>   3   c
4    a <NA>   4   d
5    k   f1   5   e
6    x   f1   6   f

new_format <- list(
  df1 = list(
    id = rule("No ID available" = c("", NA, "<Missing>")),
    id2 = rule("<Missing>" = c("", NA, "<Missing>"))
  )
)

res <- dunlin::reformat(prop_db, new_format, .na_last = TRUE)

which result in res as

$df1
               id       id2 val
1               a        f1   a
2               b        f2   b
3 No ID available <Missing>   c
4               a <Missing>   d
5               k        f1   e
6               x        f1   f

$df2
    id  id2 num val
1    a   f1   1   a
2    b   f2   2   b
3 <NA> <NA>   3   c
4    a <NA>   4   d
5    k   f1   5   e
6    x   f1   6   f

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