Tool to transform any type of vector, or even combination of vectors, into an integer vector ranging from 1 to the number of unique values. This actually creates an unique identifier vector.
Usage
to_integer(
...,
inputs = NULL,
sorted = FALSE,
add_items = FALSE,
items.list = FALSE,
multi.df = FALSE,
multi.join = "_",
na.valid = FALSE,
internal = FALSE
)Arguments
- ...
Vectors of any type, to be transformed into a single integer vector ranging from 1 to the number of unique elements.
- inputs
A list of inputs, by default it is
NULL. If provided, it completely replaces the elements in....- sorted
Logical, default is
FALSE. Whether the integer vector should make reference to sorted values?- add_items
Logical, default is
FALSE. Whether to add the unique values of the original vector(s). If requested, an attributeitemsis created containing the values (alternatively, they can appear in a list ifitems.list=TRUE).- items.list
Logical, default is
FALSE. Only used ifadd_items=TRUE. IfTRUE, then a list of length 2 is returned withxthe integer vector anditemsthe vector of items.- multi.df
Logical, default is
FALSE. IfTRUEthen a data.frame listing the unique elements is returned in the form of a data.frame. Ignored ifadd_items = FALSE.- multi.join
Character scalar used to join the items of multiple vectors. The default is
"_". Ignored ifadd_items = FALSE.- na.valid
Logical, default is
FALSE. Whether to consider NAs as regular values. IfTRUE, the returned index will not contain any NA value.- internal
Logical, default is
FALSE. For programming only. If this function is used within another function, settinginternal = TRUEis needed to make the evaluation of...valid. End users ofto_integershould not care.
Value
Reruns a vector of the same length as the input vectors.
If add_items=TRUE and items.list=TRUE, a list of two elements is returned: x
being the integer vector and items being the unique values to which the values
in x make reference.
Examples
x1 = iris$Species
x2 = as.integer(iris$Sepal.Length)
# transforms the species vector into integers
to_integer(x1)
#> [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> [38] 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
#> [75] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3
#> [112] 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
#> [149] 3 3
# To obtain the "items":
to_integer(x1, add_items = TRUE)
#> [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> [38] 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
#> [75] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3
#> [112] 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
#> [149] 3 3
#> attr(,"items")
#> [1] setosa versicolor virginica
#> Levels: setosa versicolor virginica
# same but in list form
to_integer(x1, add_items = TRUE, items.list = TRUE)
#> $x
#> [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> [38] 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
#> [75] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3
#> [112] 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
#> [149] 3 3
#>
#> $items
#> [1] setosa versicolor virginica
#> Levels: setosa versicolor virginica
#>
# transforms x2 into an integer vector from 1 to 4
to_integer(x2, add_items = TRUE)
#> [1] 1 2 2 2 1 1 2 1 2 2 1 2 2 2 1 1 1 1 1 1 1 1 2 1 2 1 1 1 1 2 2 1 1 1 2 1 1
#> [38] 2 2 1 1 2 2 1 1 2 1 2 1 1 3 4 4 1 4 1 4 2 4 1 1 1 4 4 1 4 1 1 4 1 1 4 4 4
#> [75] 4 4 4 4 4 1 1 1 1 4 1 4 4 4 1 1 1 4 1 1 1 1 1 4 1 1 4 1 3 4 4 3 2 3 4 3 4
#> [112] 4 4 1 1 4 4 3 3 4 4 1 3 4 4 3 4 4 4 3 3 3 4 4 4 3 4 4 4 4 4 4 1 4 4 4 4 4
#> [149] 4 1
#> attr(,"items")
#> [1] 5 4 7 6
# To have the sorted items:
to_integer(x2, add_items = TRUE, sorted = TRUE)
#> [1] 2 1 1 1 2 2 1 2 1 1 2 1 1 1 2 2 2 2 2 2 2 2 1 2 1 2 2 2 2 1 1 2 2 2 1 2 2
#> [38] 1 1 2 2 1 1 2 2 1 2 1 2 2 4 3 3 2 3 2 3 1 3 2 2 2 3 3 2 3 2 2 3 2 2 3 3 3
#> [75] 3 3 3 3 3 2 2 2 2 3 2 3 3 3 2 2 2 3 2 2 2 2 2 3 2 2 3 2 4 3 3 4 1 4 3 4 3
#> [112] 3 3 2 2 3 3 4 4 3 3 2 4 3 3 4 3 3 3 4 4 4 3 3 3 4 3 3 3 3 3 3 2 3 3 3 3 3
#> [149] 3 2
#> attr(,"items")
#> [1] 4 5 6 7
# placing the three side to side
head(cbind(x2, as_index = to_integer(x2),
as_index_sorted = to_integer(x2, sorted = TRUE)))
#> x2 as_index as_index_sorted
#> [1,] 5 1 2
#> [2,] 4 2 1
#> [3,] 4 2 1
#> [4,] 4 2 1
#> [5,] 5 1 2
#> [6,] 5 1 2
# The result can safely be used as an index
res = to_integer(x2, add_items = TRUE, sorted = TRUE, items.list = TRUE)
all(res$items[res$x] == x2)
#> [1] TRUE
#
# Multiple vectors
#
to_integer(x1, x2, add_items = TRUE)
#> [1] 1 2 2 2 1 1 2 1 2 2 1 2 2 2 1 1 1 1 1 1 1 1 2 1 2
#> [26] 1 1 1 1 2 2 1 1 1 2 1 1 2 2 1 1 2 2 1 1 2 1 2 1 1
#> [51] 3 4 4 5 4 5 4 6 4 5 5 5 4 4 5 4 5 5 4 5 5 4 4 4 4
#> [76] 4 4 4 4 5 5 5 5 4 5 4 4 4 5 5 5 4 5 5 5 5 5 4 5 5
#> [101] 7 8 9 7 7 9 10 9 7 9 7 7 7 8 8 7 7 9 9 7 7 8 9 7 7
#> [126] 9 7 7 7 9 9 9 7 7 7 9 7 7 7 7 7 7 8 7 7 7 7 7 7 8
#> attr(,"items")
#> [1] "setosa_5" "setosa_4" "versicolor_7" "versicolor_6" "versicolor_5"
#> [6] "versicolor_4" "virginica_6" "virginica_5" "virginica_7" "virginica_4"
# You can use multi.join to handle the join of the items:
to_integer(x1, x2, add_items = TRUE, multi.join = "; ")
#> [1] 1 2 2 2 1 1 2 1 2 2 1 2 2 2 1 1 1 1 1 1 1 1 2 1 2
#> [26] 1 1 1 1 2 2 1 1 1 2 1 1 2 2 1 1 2 2 1 1 2 1 2 1 1
#> [51] 3 4 4 5 4 5 4 6 4 5 5 5 4 4 5 4 5 5 4 5 5 4 4 4 4
#> [76] 4 4 4 4 5 5 5 5 4 5 4 4 4 5 5 5 4 5 5 5 5 5 4 5 5
#> [101] 7 8 9 7 7 9 10 9 7 9 7 7 7 8 8 7 7 9 9 7 7 8 9 7 7
#> [126] 9 7 7 7 9 9 9 7 7 7 9 7 7 7 7 7 7 8 7 7 7 7 7 7 8
#> attr(,"items")
#> [1] "setosa; 5" "setosa; 4" "versicolor; 7" "versicolor; 6"
#> [5] "versicolor; 5" "versicolor; 4" "virginica; 6" "virginica; 5"
#> [9] "virginica; 7" "virginica; 4"
# alternatively, return the items as a data.frame
to_integer(x1, x2, add_items = TRUE, multi.df = TRUE)
#> [1] 1 2 2 2 1 1 2 1 2 2 1 2 2 2 1 1 1 1 1 1 1 1 2 1 2
#> [26] 1 1 1 1 2 2 1 1 1 2 1 1 2 2 1 1 2 2 1 1 2 1 2 1 1
#> [51] 3 4 4 5 4 5 4 6 4 5 5 5 4 4 5 4 5 5 4 5 5 4 4 4 4
#> [76] 4 4 4 4 5 5 5 5 4 5 4 4 4 5 5 5 4 5 5 5 5 5 4 5 5
#> [101] 7 8 9 7 7 9 10 9 7 9 7 7 7 8 8 7 7 9 9 7 7 8 9 7 7
#> [126] 9 7 7 7 9 9 9 7 7 7 9 7 7 7 7 7 7 8 7 7 7 7 7 7 8
#> attr(,"items")
#> x1 x2
#> 1 setosa 5
#> 2 setosa 4
#> 3 versicolor 7
#> 4 versicolor 6
#> 5 versicolor 5
#> 6 versicolor 4
#> 7 virginica 6
#> 8 virginica 5
#> 9 virginica 7
#> 10 virginica 4
#
# NA values
#
x1_na = c("a", "a", "b", NA, NA, "b", "a", "c", NA)
x2_na = c(NA, 1, NA, 1, 1, 1, 2, 2, 2)
# by default the NAs are propagated
to_integer(x1_na, x2_na, add_items = TRUE)
#> [1] NA 1 NA NA NA 2 3 4 NA
#> attr(,"items")
#> [1] "a_1" "b_1" "a_2" "c_2"
# but you can treat them as valid values with na.valid = TRUE
to_integer(x1_na, x2_na, add_items = TRUE, na.valid = TRUE)
#> [1] 1 2 3 4 4 5 6 7 8
#> attr(,"items")
#> [1] "a_NA" "a_1" "b_NA" "NA_1" "b_1" "a_2" "c_2" "NA_2"
#
# programmatic use
#
# the argument `inputs` can be used for easy programmatic use
all_vars = list(x1_na, x2_na)
to_integer(inputs = all_vars)
#> [1] NA 1 NA NA NA 2 3 4 NA