Skip to contents

Void Value Utilities

Source: R/void.R
void.Rd

A comprehensive suite of functions for detecting, removing, and managing "void" values (NA, NULL, and empty strings) in R objects.

Usage

is_void(x, include_na = TRUE, include_null = TRUE, include_empty_str = TRUE)

any_void(x, include_na = TRUE, include_null = TRUE, include_empty_str = TRUE)

drop_void(x, include_na = TRUE, include_null = TRUE, include_empty_str = TRUE)

replace_void(
  x,
  value = NA,
  include_na = TRUE,
  include_null = TRUE,
  include_empty_str = TRUE
)

cols_with_void(
  data,
  include_na = TRUE,
  include_null = TRUE,
  include_empty_str = TRUE,
  return_names = TRUE
)

rows_with_void(
  data,
  include_na = TRUE,
  include_null = TRUE,
  include_empty_str = TRUE
)

Arguments

x

A vector or list.

include_na

Logical. Detect NA if TRUE. Default: TRUE.

include_null

Logical. Detect NULL if TRUE. Default: TRUE.

include_empty_str

Logical. Detect empty strings "" if TRUE. Default: TRUE.

value

The replacement value to use for voids. Default: NA.

data

A data.frame or tibble.

return_names

Logical. If TRUE (default), return column names; else logical vector.

Value

A logical vector indicating which elements are void.

  • If x is NULL, returns a single TRUE (if include_null=TRUE) or FALSE.

  • If x is an empty vector, returns logical(0).

  • If x is a list, evaluates each element recursively and returns a flattened logical vector.

  • For atomic vectors, returns a logical vector of the same length.

A single logical value:

  • TRUE if any void values are present.

  • FALSE otherwise.

  • For NULL input, returns TRUE if include_null = TRUE, else FALSE.

A cleaned vector or list of the same type as input, with void values removed.

A cleaned vector or list with void values replaced.

A character vector (column names) or logical vector indicating void presence per column.

A logical vector of length nrow(data) indicating whether each row contains at least one void value.

Details

The void utilities family consists of:

  • is_void: Core detection function returning logical vector

  • any_void: Check if any void value exists

  • drop_void: Remove void values from vectors/lists

  • replace_void: Replace void values with custom values

  • cols_with_void: Detect columns containing void values

  • rows_with_void: Detect rows containing void values

All functions support customizable void detection through three parameters:

  • include_na: Consider NA as void (default: TRUE)

  • include_null: Consider NULL as void (default: TRUE)

  • include_empty_str: Consider "" as void (default: TRUE)

is_void()

Check for Null / NA / Blank ("") Values

Determine whether input values are considered "void": NULL, NA, or "". Each condition is controlled by a dedicated argument.

any_void()

Check if Any Value is Void (NA / NULL / "")

Test whether any element in a vector or list is considered "void". Void values include NA, NULL, and empty strings (""), and you can customize which ones to consider.

drop_void

Remove Void Values from a Vector or List

Removes elements from a vector or list that are considered "void": NA, NULL, and empty strings (""). Each can be toggled via parameters.

replace_void

Replace void values (NA / NULL / "")

Replace elements in a vector or list considered "void" with a specified value. Void values include NA, NULL, and empty strings "" (toggle via flags).

cols_with_void()

Detect Columns Containing Void Values

Scan a data.frame or tibble and identify columns that contain any "void" values. Void values include NA, NULL, and "", which can be toggled via parameters.

rows_with_void

Detect rows containing void values (NA / NULL / "")

Scan a data.frame or tibble and identify rows that contain any "void" values. Void values include NA, NULL, and empty strings "" (toggle via flags).

Examples

is_void(c(NA, "", "text"))                  # TRUE TRUE FALSE
#> [1]  TRUE  TRUE FALSE
is_void(list(NA, "", NULL, "a"))            # TRUE TRUE TRUE FALSE
#> [1]  TRUE  TRUE  TRUE FALSE
is_void("NA", include_na = FALSE)           # FALSE
#> [1] FALSE
is_void(NULL)                               # TRUE
#> [1] TRUE
any_void(c("a", "", NA))                # TRUE
#> [1] TRUE
any_void(list("x", NULL, "y"))          # TRUE
#> [1] TRUE
any_void(c("a", "b", "c"))              # FALSE
#> [1] FALSE
any_void(NULL)                          # TRUE
#> [1] TRUE
any_void("", include_empty_str = FALSE) # FALSE
#> [1] FALSE
drop_void(c("apple", "", NA, "banana"))
#> [1] "apple"  "banana"
drop_void(list("A", NA, "", NULL, "B"))
#> [[1]]
#> [1] "A"
#> 
#> [[2]]
#> [1] "B"
#> 
drop_void(c("", NA), include_na = FALSE)
#> [1] NA
replace_void(c(NA, "", "a"), value = "N/A")
#> [1] "N/A" "N/A" "a"  
replace_void(list("A", "", NULL, NA), value = "missing")
#> [[1]]
#> [1] "A"
#> 
#> [[2]]
#> [1] "missing"
#> 
#> [[3]]
#> [1] "missing"
#> 
#> [[4]]
#> [1] "missing"
#> 
replace_void(c("", "b"), value = 0, include_empty_str = TRUE)
#> [1] "0" "b"
df <- data.frame(name = c("A", "", "C"), score = c(1, NA, 3), id = 1:3)
cols_with_void(df)
#> [1] "name"  "score"
cols_with_void(df, return_names = FALSE)
#>  name score    id 
#>  TRUE  TRUE FALSE 
cols_with_void(df, include_na = FALSE)
#> [1] "name"
df <- data.frame(id = 1:3, name = c("A", "", "C"), score = c(10, NA, 20))
rows_with_void(df)
#> [1] FALSE  TRUE FALSE
df[rows_with_void(df), ]
#>   id name score
#> 2  2         NA