Package 'mutagen'

Title: Extensions to dplyr's mutate
Description: Extensions to dplyr's mutate.
Authors: Gustavo Velásquez [aut, cre]
Maintainer: Gustavo Velásquez <[email protected]>
License: MIT + file LICENSE
Version: 0.1.0
Built: 2025-10-05 09:23:53 UTC
Source: https://github.com/gvelasq/mutagen

Help Index

Generate a list-column with NULLs replaced with NAs

Description

This function takes a list and replaces all NULL values with NA. It is useful for working with list-columns in a data frame.

Usage

gen_na_listcol(x)

Arguments

x

A list or list-column to modify.

Details

Parallelization is supported via purrr::in_parallel().

Value

A list with all NULL values replaced with NA.

Examples

library(dplyr, warn.conflicts = FALSE)
a <-
  mtcars %>%
  select(cyl, vs, am) %>%
  slice(1:6) %>%
  as_tibble() %>%
  mutate(listcol = list(NULL, "b", "c", "d", "e", "f"))
glimpse(a)
b <-
  a %>%
  mutate(across(starts_with("listcol"), gen_na_listcol))
glimpse(b)

Generate rowwise count of columns matching a set of values

Description

This function performs a rowwise count of columns in a data frame that match a set of supplied values.

Usage

gen_rowcount(data, cols, values)

Arguments

data

A data frame.
cols

<tidy-select> Columns to search across.
values

A list of values to match.

Details

Parallelization is supported via purrr::in_parallel().

Value

An integer vector with the number of matched values.

Examples

library(dplyr, warn.conflicts = FALSE)
a <- tibble(
  x = 1:3,
  y = rep(NA, 3),
  z = letters[1:3],
  aa = rep(FALSE, 3)
)
val <- list(1, NA, "a", FALSE)
gen_rowcount(a, values = val)
gen_rowcount(a, everything(), values = val)
gen_rowcount(a, starts_with(letters[25:26]), values = val)
b <- a %>% mutate(q = gen_rowcount(., values = val))
b

Generate first rowwise nonmissing value

Description

This function returns the first rowwise nonmissing value in a data frame.

Usage

gen_rowfirst(data, cols)

Arguments

data

A data frame.
cols

<tidy-select> Columns to search across.

Details

Parallelization is supported via purrr::in_parallel().

Value

A vector of the first rowwise nonmissing value. The vector's type will be of common type to all rowwise nonmissing values.

Examples

library(dplyr, warn.conflicts = FALSE)
a <- tibble(
  x = c(1, NA, 2),
  y = c(NA, 3, NA),
  z = c(4, NA, 5)
)
gen_rowfirst(a)
gen_rowfirst(a, all_of(letters[25:26]))
b <- a %>% mutate(q = gen_rowfirst(.))
b
c <-
  a %>%
  mutate(w = c("a", TRUE, NA), .before = "x") %>%
  mutate(q = gen_rowfirst(.))
c # note that q is of type <chr>

Generate last rowwise nonmissing value

Description

This function returns the last rowwise nonmissing value in a data frame.

Usage

gen_rowlast(data, cols)

Arguments

data

A data frame.
cols

<tidy-select> Columns to search across.

Details

Parallelization is supported via purrr::in_parallel().

Value

A vector of the last rowwise nonmissing value. The vector's type will be of common type to all rowwise nonmissing values.

Examples

library(dplyr, warn.conflicts = FALSE)
a <- tibble(
  x = c(1, NA, 2),
  y = c(NA, 3, NA),
  z = c(4, NA, 5)
)
gen_rowlast(a)
gen_rowlast(a, all_of(letters[24:25]))
b <- a %>% mutate(q = gen_rowlast(.))
b
c <-
  a %>%
  mutate(aa = c("a", TRUE, NA), .after = "z") %>%
  mutate(q = gen_rowlast(.))
c # note that q is of type <chr>

Generate rowwise match of a set of values

Description

This function performs a rowwise match of a set of supplied values across columns in a data frame. If any of the row values equal one of the supplied values, this function returns an integer 1 (1L) for that row, otherwise it returns an integer 0 (0L).

Usage

gen_rowmatch(data, cols, values)

Arguments

data

A data frame.
cols

<tidy-select> Columns to search across.
values

A list of values to match.

Details

Parallelization is supported via purrr::in_parallel().

Value

A binary integer vector indicating whether any supplied value was matched with an integer 1 (1L), otherwise it returns an integer 0 (0L).

Examples

library(dplyr, warn.conflicts = FALSE)
a <- tibble(
  x = 1:3,
  y = rep(NA, 3),
  z = letters[1:3],
  aa = rep(FALSE, 3)
)
val <- list(1, NA, "a", FALSE)
val2 <- list(5, NaN, "d", Inf)
gen_rowmatch(a, values = val)
b <- a %>%
  mutate(
    q = gen_rowmatch(., values = val),
    r = gen_rowmatch(., values = val2)
  )
b

Generate rowwise maximum value

Description

This function returns the rowwise maximum value in a data frame.

Usage

gen_rowmax(data, cols)

Arguments

data

A data frame.
cols

<tidy-select> Columns to search across.

Details

Parallelization is supported via purrr::in_parallel().

Value

A vector of the rowwise maximum value.

Examples

library(dplyr, warn.conflicts = FALSE)
a <- tibble(
  x = c(1, NA, 2),
  y = c(NA, 3, NA),
  z = c(4, NA, 5)
)
gen_rowmax(a)
gen_rowmax(a, everything())
gen_rowmax(a, starts_with(letters[24:25]))
b <- a %>% mutate(q = gen_rowmax(.))
b

Generate rowwise minimum value

Description

This function returns the rowwise minimum value in a data frame.

Usage

gen_rowmin(data, cols)

Arguments

data

A data frame.
cols

<tidy-select> Columns to search across.

Details

Parallelization is supported via purrr::in_parallel().

Value

A vector of the rowwise minimum value.

Examples

library(dplyr, warn.conflicts = FALSE)
a <- tibble(
  x = c(1, NA, 2),
  y = c(NA, 3, NA),
  z = c(4, NA, 5)
)
gen_rowmin(a)
gen_rowmin(a, everything())
gen_rowmin(a, starts_with(letters[25:26]))
b <- a %>% mutate(q = gen_rowmin(.))
b

Generate nth rowwise nonmissing value

Description

This function returns the nth rowwise nonmissing value in a data frame.

Usage

gen_rownth(data, cols, n)

Arguments

data

A data frame.
cols

<tidy-select> Columns to search across.
n

An integer vector of length 1 that specifies the position of the nth rowwise nonmissing value to search for. A negative integer will index from the end.

Details

Parallelization is supported via purrr::in_parallel().

Value

A vector of the nth rowwise nonmissing value. The vector's type will be of common type to all rowwise nonmissing values.

Examples

library(dplyr, warn.conflicts = FALSE)
a <- tibble(
  x = c(1, NA, 2),
  y = c(NA, 3, NA),
  z = c(4, NA, 5)
)
gen_rownth(a, n = 1)
gen_rownth(a, n = 2)
gen_rownth(a, all_of(letters[25:26]), n = 1)
b <- a %>% mutate(q = gen_rownth(., n = 1), r = gen_rownth(., n = 2))
b
c <-
  a %>%
  mutate(w = c("a", TRUE, NA), .before = "x") %>%
  mutate(q = gen_rownth(., n = 1), r = gen_rownth(., n = 2))
c # note that q and r are of type <chr>