Unlike map() and its variants which always return a fixed object
type (list for map(), integer vector for map_int(), etc), the
modify() family always returns the same type as the input object.
modify()is a shortcut forx[[i]] <- f(x[[i]]); return(x).modify_if()only modifies the elements ofxthat satisfy a predicate and leaves the others unchanged.modify_at()only modifies elements given by names or positions.modify2()modifies the elements of.xbut also passes the elements of.yto.f, just likemap2().imodify()passes the names or the indices to.flikeimap()does.modify_in()modifies a single element in apluck()location.
Usage
modify(.x, .f, ...)
modify_if(.x, .p, .f, ..., .else = NULL)
modify_at(.x, .at, .f, ...)
modify2(.x, .y, .f, ...)
imodify(.x, .f, ...)Arguments
- .x
A vector.
- .f
A function specified in the same way as the corresponding map function.
- ...
Additional arguments passed on to the mapped function.
We now generally recommend against using
...to pass additional (constant) arguments to.f. Instead use a shorthand anonymous function:This makes it easier to understand which arguments belong to which function and will tend to yield better error messages.
- .p
A single predicate function, a formula describing such a predicate function, or a logical vector of the same length as
.x. Alternatively, if the elements of.xare themselves lists of objects, a string indicating the name of a logical element in the inner lists. Only those elements where.pevaluates toTRUEwill be modified.- .else
A function applied to elements of
.xfor which.preturnsFALSE.- .at
A logical, integer, or character vector giving the elements to select. Alternatively, a function that takes a vector of names, and returns a logical, integer, or character vector of elements to select.
![[Deprecated]](figures/lifecycle-deprecated.svg)
: if the tidyselect package is
installed, you can use vars()and tidyselect helpers to select elements.- .y
A vector, usually the same length as
.x.
Details
Since the transformation can alter the structure of the input; it's
your responsibility to ensure that the transformation produces a
valid output. For example, if you're modifying a data frame, .f
must preserve the length of the input.
Genericity
modify() and variants are generic over classes that implement
length(), [[ and [[<- methods. If the default implementation
is not compatible for your class, you can override them with your
own methods.
If you implement your own modify() method, make sure it satisfies
the following invariants:
These invariants are known as the functor laws in computer science.
Examples
# Convert factors to characters
iris |>
modify_if(is.factor, as.character) |>
str()
#> 'data.frame': 150 obs. of 5 variables:
#> $ Sepal.Length: num 5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...
#> $ Sepal.Width : num 3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
#> $ Petal.Length: num 1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ...
#> $ Petal.Width : num 0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ...
#> $ Species : chr "setosa" "setosa" "setosa" "setosa" ...
# Specify which columns to map with a numeric vector of positions:
mtcars |> modify_at(c(1, 4, 5), as.character) |> str()
#> 'data.frame': 32 obs. of 11 variables:
#> $ mpg : chr "21" "21" "22.8" "21.4" ...
#> $ cyl : num 6 6 4 6 8 6 8 4 4 6 ...
#> $ disp: num 160 160 108 258 360 ...
#> $ hp : chr "110" "110" "93" "110" ...
#> $ drat: chr "3.9" "3.9" "3.85" "3.08" ...
#> $ wt : num 2.62 2.88 2.32 3.21 3.44 ...
#> $ qsec: num 16.5 17 18.6 19.4 17 ...
#> $ vs : num 0 0 1 1 0 1 0 1 1 1 ...
#> $ am : num 1 1 1 0 0 0 0 0 0 0 ...
#> $ gear: num 4 4 4 3 3 3 3 4 4 4 ...
#> $ carb: num 4 4 1 1 2 1 4 2 2 4 ...
# Or with a vector of names:
mtcars |> modify_at(c("cyl", "am"), as.character) |> str()
#> 'data.frame': 32 obs. of 11 variables:
#> $ mpg : num 21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
#> $ cyl : chr "6" "6" "4" "6" ...
#> $ disp: num 160 160 108 258 360 ...
#> $ hp : num 110 110 93 110 175 105 245 62 95 123 ...
#> $ drat: num 3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...
#> $ wt : num 2.62 2.88 2.32 3.21 3.44 ...
#> $ qsec: num 16.5 17 18.6 19.4 17 ...
#> $ vs : num 0 0 1 1 0 1 0 1 1 1 ...
#> $ am : chr "1" "1" "1" "0" ...
#> $ gear: num 4 4 4 3 3 3 3 4 4 4 ...
#> $ carb: num 4 4 1 1 2 1 4 2 2 4 ...
list(x = sample(c(TRUE, FALSE), 100, replace = TRUE), y = 1:100) |>
list_transpose(simplify = FALSE) |>
modify_if("x", \(l) list(x = l$x, y = l$y * 100)) |>
list_transpose()
#> $x
#> [1] FALSE TRUE TRUE FALSE FALSE FALSE FALSE TRUE FALSE TRUE TRUE
#> [12] FALSE TRUE TRUE TRUE FALSE TRUE FALSE TRUE FALSE TRUE TRUE
#> [23] FALSE TRUE TRUE FALSE FALSE TRUE FALSE TRUE FALSE TRUE FALSE
#> [34] FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE
#> [45] FALSE FALSE TRUE FALSE FALSE TRUE FALSE TRUE FALSE TRUE TRUE
#> [56] FALSE TRUE TRUE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE
#> [67] FALSE TRUE FALSE FALSE TRUE TRUE TRUE TRUE TRUE FALSE FALSE
#> [78] FALSE FALSE TRUE FALSE TRUE FALSE TRUE TRUE TRUE FALSE FALSE
#> [89] TRUE TRUE FALSE FALSE TRUE TRUE FALSE FALSE TRUE FALSE TRUE
#> [100] TRUE
#>
#> $y
#> [1] 1 200 300 4 5 6 7 800 9 1000 1100
#> [12] 12 1300 1400 1500 16 1700 18 1900 20 2100 2200
#> [23] 23 2400 2500 26 27 2800 29 3000 31 3200 33
#> [34] 34 35 3600 37 38 39 40 41 4200 43 44
#> [45] 45 46 4700 48 49 5000 51 5200 53 5400 5500
#> [56] 56 5700 5800 59 60 61 62 63 6400 6500 66
#> [67] 67 6800 69 70 7100 7200 7300 7400 7500 76 77
#> [78] 78 79 8000 81 8200 83 8400 8500 8600 87 88
#> [89] 8900 9000 91 92 9300 9400 95 96 9700 98 9900
#> [100] 10000
#>
# Use modify2() to map over two vectors and preserve the type of
# the first one:
x <- c(foo = 1L, bar = 2L)
y <- c(TRUE, FALSE)
modify2(x, y, \(x, cond) if (cond) x else 0L)
#> foo bar
#> 1 0
# Use a predicate function to decide whether to map a function:
modify_if(iris, is.factor, as.character)
#> Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#> 1 5.1 3.5 1.4 0.2 setosa
#> 2 4.9 3.0 1.4 0.2 setosa
#> 3 4.7 3.2 1.3 0.2 setosa
#> 4 4.6 3.1 1.5 0.2 setosa
#> 5 5.0 3.6 1.4 0.2 setosa
#> 6 5.4 3.9 1.7 0.4 setosa
#> 7 4.6 3.4 1.4 0.3 setosa
#> 8 5.0 3.4 1.5 0.2 setosa
#> 9 4.4 2.9 1.4 0.2 setosa
#> 10 4.9 3.1 1.5 0.1 setosa
#> 11 5.4 3.7 1.5 0.2 setosa
#> 12 4.8 3.4 1.6 0.2 setosa
#> 13 4.8 3.0 1.4 0.1 setosa
#> 14 4.3 3.0 1.1 0.1 setosa
#> 15 5.8 4.0 1.2 0.2 setosa
#> 16 5.7 4.4 1.5 0.4 setosa
#> 17 5.4 3.9 1.3 0.4 setosa
#> 18 5.1 3.5 1.4 0.3 setosa
#> 19 5.7 3.8 1.7 0.3 setosa
#> 20 5.1 3.8 1.5 0.3 setosa
#> 21 5.4 3.4 1.7 0.2 setosa
#> 22 5.1 3.7 1.5 0.4 setosa
#> 23 4.6 3.6 1.0 0.2 setosa
#> 24 5.1 3.3 1.7 0.5 setosa
#> 25 4.8 3.4 1.9 0.2 setosa
#> 26 5.0 3.0 1.6 0.2 setosa
#> 27 5.0 3.4 1.6 0.4 setosa
#> 28 5.2 3.5 1.5 0.2 setosa
#> 29 5.2 3.4 1.4 0.2 setosa
#> 30 4.7 3.2 1.6 0.2 setosa
#> 31 4.8 3.1 1.6 0.2 setosa
#> 32 5.4 3.4 1.5 0.4 setosa
#> 33 5.2 4.1 1.5 0.1 setosa
#> 34 5.5 4.2 1.4 0.2 setosa
#> 35 4.9 3.1 1.5 0.2 setosa
#> 36 5.0 3.2 1.2 0.2 setosa
#> 37 5.5 3.5 1.3 0.2 setosa
#> 38 4.9 3.6 1.4 0.1 setosa
#> 39 4.4 3.0 1.3 0.2 setosa
#> 40 5.1 3.4 1.5 0.2 setosa
#> 41 5.0 3.5 1.3 0.3 setosa
#> 42 4.5 2.3 1.3 0.3 setosa
#> 43 4.4 3.2 1.3 0.2 setosa
#> 44 5.0 3.5 1.6 0.6 setosa
#> 45 5.1 3.8 1.9 0.4 setosa
#> 46 4.8 3.0 1.4 0.3 setosa
#> 47 5.1 3.8 1.6 0.2 setosa
#> 48 4.6 3.2 1.4 0.2 setosa
#> 49 5.3 3.7 1.5 0.2 setosa
#> 50 5.0 3.3 1.4 0.2 setosa
#> 51 7.0 3.2 4.7 1.4 versicolor
#> 52 6.4 3.2 4.5 1.5 versicolor
#> 53 6.9 3.1 4.9 1.5 versicolor
#> 54 5.5 2.3 4.0 1.3 versicolor
#> 55 6.5 2.8 4.6 1.5 versicolor
#> 56 5.7 2.8 4.5 1.3 versicolor
#> 57 6.3 3.3 4.7 1.6 versicolor
#> 58 4.9 2.4 3.3 1.0 versicolor
#> 59 6.6 2.9 4.6 1.3 versicolor
#> 60 5.2 2.7 3.9 1.4 versicolor
#> 61 5.0 2.0 3.5 1.0 versicolor
#> 62 5.9 3.0 4.2 1.5 versicolor
#> 63 6.0 2.2 4.0 1.0 versicolor
#> 64 6.1 2.9 4.7 1.4 versicolor
#> 65 5.6 2.9 3.6 1.3 versicolor
#> 66 6.7 3.1 4.4 1.4 versicolor
#> 67 5.6 3.0 4.5 1.5 versicolor
#> 68 5.8 2.7 4.1 1.0 versicolor
#> 69 6.2 2.2 4.5 1.5 versicolor
#> 70 5.6 2.5 3.9 1.1 versicolor
#> 71 5.9 3.2 4.8 1.8 versicolor
#> 72 6.1 2.8 4.0 1.3 versicolor
#> 73 6.3 2.5 4.9 1.5 versicolor
#> 74 6.1 2.8 4.7 1.2 versicolor
#> 75 6.4 2.9 4.3 1.3 versicolor
#> 76 6.6 3.0 4.4 1.4 versicolor
#> 77 6.8 2.8 4.8 1.4 versicolor
#> 78 6.7 3.0 5.0 1.7 versicolor
#> 79 6.0 2.9 4.5 1.5 versicolor
#> 80 5.7 2.6 3.5 1.0 versicolor
#> 81 5.5 2.4 3.8 1.1 versicolor
#> 82 5.5 2.4 3.7 1.0 versicolor
#> 83 5.8 2.7 3.9 1.2 versicolor
#> 84 6.0 2.7 5.1 1.6 versicolor
#> 85 5.4 3.0 4.5 1.5 versicolor
#> 86 6.0 3.4 4.5 1.6 versicolor
#> 87 6.7 3.1 4.7 1.5 versicolor
#> 88 6.3 2.3 4.4 1.3 versicolor
#> 89 5.6 3.0 4.1 1.3 versicolor
#> 90 5.5 2.5 4.0 1.3 versicolor
#> 91 5.5 2.6 4.4 1.2 versicolor
#> 92 6.1 3.0 4.6 1.4 versicolor
#> 93 5.8 2.6 4.0 1.2 versicolor
#> 94 5.0 2.3 3.3 1.0 versicolor
#> 95 5.6 2.7 4.2 1.3 versicolor
#> 96 5.7 3.0 4.2 1.2 versicolor
#> 97 5.7 2.9 4.2 1.3 versicolor
#> 98 6.2 2.9 4.3 1.3 versicolor
#> 99 5.1 2.5 3.0 1.1 versicolor
#> 100 5.7 2.8 4.1 1.3 versicolor
#> 101 6.3 3.3 6.0 2.5 virginica
#> 102 5.8 2.7 5.1 1.9 virginica
#> 103 7.1 3.0 5.9 2.1 virginica
#> 104 6.3 2.9 5.6 1.8 virginica
#> 105 6.5 3.0 5.8 2.2 virginica
#> 106 7.6 3.0 6.6 2.1 virginica
#> 107 4.9 2.5 4.5 1.7 virginica
#> 108 7.3 2.9 6.3 1.8 virginica
#> 109 6.7 2.5 5.8 1.8 virginica
#> 110 7.2 3.6 6.1 2.5 virginica
#> 111 6.5 3.2 5.1 2.0 virginica
#> 112 6.4 2.7 5.3 1.9 virginica
#> 113 6.8 3.0 5.5 2.1 virginica
#> 114 5.7 2.5 5.0 2.0 virginica
#> 115 5.8 2.8 5.1 2.4 virginica
#> 116 6.4 3.2 5.3 2.3 virginica
#> 117 6.5 3.0 5.5 1.8 virginica
#> 118 7.7 3.8 6.7 2.2 virginica
#> 119 7.7 2.6 6.9 2.3 virginica
#> 120 6.0 2.2 5.0 1.5 virginica
#> 121 6.9 3.2 5.7 2.3 virginica
#> 122 5.6 2.8 4.9 2.0 virginica
#> 123 7.7 2.8 6.7 2.0 virginica
#> 124 6.3 2.7 4.9 1.8 virginica
#> 125 6.7 3.3 5.7 2.1 virginica
#> 126 7.2 3.2 6.0 1.8 virginica
#> 127 6.2 2.8 4.8 1.8 virginica
#> 128 6.1 3.0 4.9 1.8 virginica
#> 129 6.4 2.8 5.6 2.1 virginica
#> 130 7.2 3.0 5.8 1.6 virginica
#> 131 7.4 2.8 6.1 1.9 virginica
#> 132 7.9 3.8 6.4 2.0 virginica
#> 133 6.4 2.8 5.6 2.2 virginica
#> 134 6.3 2.8 5.1 1.5 virginica
#> 135 6.1 2.6 5.6 1.4 virginica
#> 136 7.7 3.0 6.1 2.3 virginica
#> 137 6.3 3.4 5.6 2.4 virginica
#> 138 6.4 3.1 5.5 1.8 virginica
#> 139 6.0 3.0 4.8 1.8 virginica
#> 140 6.9 3.1 5.4 2.1 virginica
#> 141 6.7 3.1 5.6 2.4 virginica
#> 142 6.9 3.1 5.1 2.3 virginica
#> 143 5.8 2.7 5.1 1.9 virginica
#> 144 6.8 3.2 5.9 2.3 virginica
#> 145 6.7 3.3 5.7 2.5 virginica
#> 146 6.7 3.0 5.2 2.3 virginica
#> 147 6.3 2.5 5.0 1.9 virginica
#> 148 6.5 3.0 5.2 2.0 virginica
#> 149 6.2 3.4 5.4 2.3 virginica
#> 150 5.9 3.0 5.1 1.8 virginica
# Specify an alternative with the `.else` argument:
modify_if(iris, is.factor, as.character, .else = as.integer)
#> Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#> 1 5 3 1 0 setosa
#> 2 4 3 1 0 setosa
#> 3 4 3 1 0 setosa
#> 4 4 3 1 0 setosa
#> 5 5 3 1 0 setosa
#> 6 5 3 1 0 setosa
#> 7 4 3 1 0 setosa
#> 8 5 3 1 0 setosa
#> 9 4 2 1 0 setosa
#> 10 4 3 1 0 setosa
#> 11 5 3 1 0 setosa
#> 12 4 3 1 0 setosa
#> 13 4 3 1 0 setosa
#> 14 4 3 1 0 setosa
#> 15 5 4 1 0 setosa
#> 16 5 4 1 0 setosa
#> 17 5 3 1 0 setosa
#> 18 5 3 1 0 setosa
#> 19 5 3 1 0 setosa
#> 20 5 3 1 0 setosa
#> 21 5 3 1 0 setosa
#> 22 5 3 1 0 setosa
#> 23 4 3 1 0 setosa
#> 24 5 3 1 0 setosa
#> 25 4 3 1 0 setosa
#> 26 5 3 1 0 setosa
#> 27 5 3 1 0 setosa
#> 28 5 3 1 0 setosa
#> 29 5 3 1 0 setosa
#> 30 4 3 1 0 setosa
#> 31 4 3 1 0 setosa
#> 32 5 3 1 0 setosa
#> 33 5 4 1 0 setosa
#> 34 5 4 1 0 setosa
#> 35 4 3 1 0 setosa
#> 36 5 3 1 0 setosa
#> 37 5 3 1 0 setosa
#> 38 4 3 1 0 setosa
#> 39 4 3 1 0 setosa
#> 40 5 3 1 0 setosa
#> 41 5 3 1 0 setosa
#> 42 4 2 1 0 setosa
#> 43 4 3 1 0 setosa
#> 44 5 3 1 0 setosa
#> 45 5 3 1 0 setosa
#> 46 4 3 1 0 setosa
#> 47 5 3 1 0 setosa
#> 48 4 3 1 0 setosa
#> 49 5 3 1 0 setosa
#> 50 5 3 1 0 setosa
#> 51 7 3 4 1 versicolor
#> 52 6 3 4 1 versicolor
#> 53 6 3 4 1 versicolor
#> 54 5 2 4 1 versicolor
#> 55 6 2 4 1 versicolor
#> 56 5 2 4 1 versicolor
#> 57 6 3 4 1 versicolor
#> 58 4 2 3 1 versicolor
#> 59 6 2 4 1 versicolor
#> 60 5 2 3 1 versicolor
#> 61 5 2 3 1 versicolor
#> 62 5 3 4 1 versicolor
#> 63 6 2 4 1 versicolor
#> 64 6 2 4 1 versicolor
#> 65 5 2 3 1 versicolor
#> 66 6 3 4 1 versicolor
#> 67 5 3 4 1 versicolor
#> 68 5 2 4 1 versicolor
#> 69 6 2 4 1 versicolor
#> 70 5 2 3 1 versicolor
#> 71 5 3 4 1 versicolor
#> 72 6 2 4 1 versicolor
#> 73 6 2 4 1 versicolor
#> 74 6 2 4 1 versicolor
#> 75 6 2 4 1 versicolor
#> 76 6 3 4 1 versicolor
#> 77 6 2 4 1 versicolor
#> 78 6 3 5 1 versicolor
#> 79 6 2 4 1 versicolor
#> 80 5 2 3 1 versicolor
#> 81 5 2 3 1 versicolor
#> 82 5 2 3 1 versicolor
#> 83 5 2 3 1 versicolor
#> 84 6 2 5 1 versicolor
#> 85 5 3 4 1 versicolor
#> 86 6 3 4 1 versicolor
#> 87 6 3 4 1 versicolor
#> 88 6 2 4 1 versicolor
#> 89 5 3 4 1 versicolor
#> 90 5 2 4 1 versicolor
#> 91 5 2 4 1 versicolor
#> 92 6 3 4 1 versicolor
#> 93 5 2 4 1 versicolor
#> 94 5 2 3 1 versicolor
#> 95 5 2 4 1 versicolor
#> 96 5 3 4 1 versicolor
#> 97 5 2 4 1 versicolor
#> 98 6 2 4 1 versicolor
#> 99 5 2 3 1 versicolor
#> 100 5 2 4 1 versicolor
#> 101 6 3 6 2 virginica
#> 102 5 2 5 1 virginica
#> 103 7 3 5 2 virginica
#> 104 6 2 5 1 virginica
#> 105 6 3 5 2 virginica
#> 106 7 3 6 2 virginica
#> 107 4 2 4 1 virginica
#> 108 7 2 6 1 virginica
#> 109 6 2 5 1 virginica
#> 110 7 3 6 2 virginica
#> 111 6 3 5 2 virginica
#> 112 6 2 5 1 virginica
#> 113 6 3 5 2 virginica
#> 114 5 2 5 2 virginica
#> 115 5 2 5 2 virginica
#> 116 6 3 5 2 virginica
#> 117 6 3 5 1 virginica
#> 118 7 3 6 2 virginica
#> 119 7 2 6 2 virginica
#> 120 6 2 5 1 virginica
#> 121 6 3 5 2 virginica
#> 122 5 2 4 2 virginica
#> 123 7 2 6 2 virginica
#> 124 6 2 4 1 virginica
#> 125 6 3 5 2 virginica
#> 126 7 3 6 1 virginica
#> 127 6 2 4 1 virginica
#> 128 6 3 4 1 virginica
#> 129 6 2 5 2 virginica
#> 130 7 3 5 1 virginica
#> 131 7 2 6 1 virginica
#> 132 7 3 6 2 virginica
#> 133 6 2 5 2 virginica
#> 134 6 2 5 1 virginica
#> 135 6 2 5 1 virginica
#> 136 7 3 6 2 virginica
#> 137 6 3 5 2 virginica
#> 138 6 3 5 1 virginica
#> 139 6 3 4 1 virginica
#> 140 6 3 5 2 virginica
#> 141 6 3 5 2 virginica
#> 142 6 3 5 2 virginica
#> 143 5 2 5 1 virginica
#> 144 6 3 5 2 virginica
#> 145 6 3 5 2 virginica
#> 146 6 3 5 2 virginica
#> 147 6 2 5 1 virginica
#> 148 6 3 5 2 virginica
#> 149 6 3 5 2 virginica
#> 150 5 3 5 1 virginica