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strengejacke authored Nov 14, 2023
2 parents 5e3375d + b65df4d commit f2aca76
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4 changes: 2 additions & 2 deletions DESCRIPTION
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@@ -1,7 +1,7 @@
Type: Package
Package: datawizard
Title: Easy Data Wrangling and Statistical Transformations
Version: 0.9.0.1
Version: 0.9.0.2
Authors@R: c(
person("Indrajeet", "Patil", , "[email protected]", role = "aut",
comment = c(ORCID = "0000-0003-1995-6531", Twitter = "@patilindrajeets")),
Expand Down Expand Up @@ -33,7 +33,7 @@ BugReports: https://github.com/easystats/datawizard/issues
Depends:
R (>= 3.6)
Imports:
insight (>= 0.19.4),
insight (>= 0.19.6),
stats,
utils
Suggests:
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5 changes: 5 additions & 0 deletions NEWS.md
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@@ -1,5 +1,10 @@
# datawizard 0.9.0.9000 (development version)

CHANGES

* `rescale()` gains `multiply` and `add` arguments, to expand ranges by a given
factor or value.

# datawizard 0.9.0

NEW FUNCTIONS
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99 changes: 94 additions & 5 deletions R/data_rescale.R
Original file line number Diff line number Diff line change
@@ -1,15 +1,26 @@
#' Rescale Variables to a New Range
#'
#' Rescale variables to a new range.
#' Can also be used to reverse-score variables (change the keying/scoring direction).
#' Rescale variables to a new range. Can also be used to reverse-score variables
#' (change the keying/scoring direction), or to expand a range.
#'
#' @inheritParams categorize
#' @inheritParams find_columns
#' @inheritParams standardize.data.frame
#'
#' @param to Numeric vector of length 2 giving the new range that the variable will have after rescaling.
#' To reverse-score a variable, the range should be given with the maximum value first.
#' See examples.
#' @param to Numeric vector of length 2 giving the new range that the variable
#' will have after rescaling. To reverse-score a variable, the range should
#' be given with the maximum value first. See examples.
#' @param multiply If not `NULL`, `to` is ignored and `multiply` will be used,
#' giving the factor by which the actual range of `x` should be expanded.
#' For example, if a vector ranges from 5 to 15 and `multiply = 1.1`, the current
#' range of 10 will be expanded by the factor of 1.1, giving a new range of
#' 11. Thus, the rescaled vector would range from 4.5 to 15.5.
#' @param add A vector of length 1 or 2. If not `NULL`, `to` is ignored and `add`
#' will be used, giving the amount by which the minimum and maximum of the
#' actual range of `x` should be expanded. For example, if a vector ranges from
#' 5 to 15 and `add = 1`, the range will be expanded from 4 to 16. If `add` is
#' of length 2, then the first value is used for the lower bound and the second
#' value for the upper bound.
#' @param range Initial (old) range of values. If `NULL`, will take the range of
#' the input vector (`range(x)`).
#' @param ... Arguments passed to or from other methods.
Expand Down Expand Up @@ -37,6 +48,21 @@
#' "Sepal.Length" = c(0, 1),
#' "Petal.Length" = c(-1, 0)
#' )))
#'
#' # "expand" ranges by a factor or a given value
#' x <- 5:15
#' x
#' # both will expand the range by 10%
#' rescale(x, multiply = 1.1)
#' rescale(x, add = 0.5)
#'
#' # expand range by different values
#' rescale(x, add = c(1, 3))
#'
#' # Specify list of multipliers
#' d <- data.frame(x = 5:15, y = 5:15)
#' rescale(d, multiply = list(x = 1.1, y = 0.5))
#'
#' @inherit data_rename
#'
#' @return A rescaled object.
Expand Down Expand Up @@ -75,6 +101,8 @@ rescale.default <- function(x, verbose = TRUE, ...) {
#' @export
rescale.numeric <- function(x,
to = c(0, 100),
multiply = NULL,
add = NULL,
range = NULL,
verbose = TRUE,
...) {
Expand All @@ -91,6 +119,9 @@ rescale.numeric <- function(x,
range <- c(min(x, na.rm = TRUE), max(x, na.rm = TRUE))
}

# check if user specified "multiply" or "add", and then update "to"
to <- .update_to(x, to, multiply, add)

# called from "makepredictcal()"? Then we have additional arguments
dot_args <- list(...)
required_dot_args <- c("min_value", "max_value", "new_min", "new_max")
Expand Down Expand Up @@ -144,6 +175,8 @@ rescale.grouped_df <- function(x,
select = NULL,
exclude = NULL,
to = c(0, 100),
multiply = NULL,
add = NULL,
range = NULL,
append = FALSE,
ignore_case = FALSE,
Expand Down Expand Up @@ -188,6 +221,8 @@ rescale.grouped_df <- function(x,
select = select,
exclude = exclude,
to = to,
multiply = multiply,
add = add,
range = range,
append = FALSE, # need to set to FALSE here, else variable will be doubled
add_transform_class = FALSE,
Expand All @@ -207,6 +242,8 @@ rescale.data.frame <- function(x,
select = NULL,
exclude = NULL,
to = c(0, 100),
multiply = NULL,
add = NULL,
range = NULL,
append = FALSE,
ignore_case = FALSE,
Expand Down Expand Up @@ -245,9 +282,61 @@ rescale.data.frame <- function(x,
if (!is.list(to)) {
to <- stats::setNames(rep(list(to), length(select)), select)
}
# Transform the 'multiply' so that it is a list now
if (!is.null(multiply) && !is.list(multiply)) {
multiply <- stats::setNames(rep(list(multiply), length(select)), select)
}
# Transform the 'add' so that it is a list now
if (!is.null(add) && !is.list(add)) {
add <- stats::setNames(rep(list(add), length(select)), select)
}
# update "to" if user specified "multiply" or "add"
to[] <- lapply(names(to), function(i) {
.update_to(x[[i]], to[[i]], multiply[[i]], add[[i]])
})

x[select] <- as.data.frame(sapply(select, function(n) {
rescale(x[[n]], to = to[[n]], range = range[[n]], add_transform_class = FALSE)
}, simplify = FALSE))
x
}


# helper ----------------------------------------------------------------------

# expand the new target range by multiplying or adding
.update_to <- function(x, to, multiply, add) {
# check if user specified "multiply" or "add", and if not, return "to"
if (is.null(multiply) && is.null(add)) {
return(to)
}
# only one of "multiply" or "add" can be specified
if (!is.null(multiply) && !is.null(add)) {
insight::format_error("Only one of `multiply` or `add` can be specified.")
}
# multiply? If yes, calculate the "add" value
if (!is.null(multiply)) {
# check for correct length
if (length(multiply) > 1) {
insight::format_error("The length of `multiply` must be 1.")
}
add <- (diff(range(x, na.rm = TRUE)) * (multiply - 1)) / 2
}
# add?
if (!is.null(add)) {
# add must be of length 1 or 2
if (length(add) > 2) {
insight::format_error("The length of `add` must be 1 or 2.")
}
# if add is of length 2, then the first value is used for the lower bound
# and the second value for the upper bound
if (length(add) == 2) {
add_low <- add[1]
add_high <- add[2]
} else {
add_low <- add_high <- add
}
to <- c(min(x, na.rm = TRUE) - add_low, max(x, na.rm = TRUE) + add_high)
}
to
}
50 changes: 44 additions & 6 deletions man/rescale.Rd

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64 changes: 64 additions & 0 deletions tests/testthat/test-data_rescale.R
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Expand Up @@ -109,3 +109,67 @@ test_that("data_rescale regex", {
ignore_attr = TRUE
)
})


# expanding range ------------------------------
test_that("data_rescale can expand range", {
# for vectors
x <- 5:15
expect_equal(
rescale(x, multiply = 1.1),
c(4.5, 5.6, 6.7, 7.8, 8.9, 10, 11.1, 12.2, 13.3, 14.4, 15.5),
ignore_attr = TRUE
)
expect_equal(rescale(x, multiply = 1.1), rescale(x, add = 0.5), ignore_attr = TRUE)
expect_error(rescale(x, multiply = 0.9, add = 1), regex = "Only one of")
expect_error(rescale(x, multiply = c(1.2, 1.4)), regex = "The length of")

# different values for add
expect_equal(
rescale(x, add = c(1, 3)),
c(4, 5.4, 6.8, 8.2, 9.6, 11, 12.4, 13.8, 15.2, 16.6, 18),
ignore_attr = TRUE
)
expect_error(rescale(x, add = 1:3), regex = "The length of")

# works with NA
expect_equal(
rescale(rep(NA_real_, 3), multiply = 1.1),
rep(NA_real_, 3),
ignore_attr = TRUE
)
expect_equal(
rescale(rep(NA_real_, 3), add = 2),
rep(NA_real_, 3),
ignore_attr = TRUE
)

# for data frames
d <- data.frame(x = 5:15, y = 5:15)
expect_equal(
rescale(d, multiply = 1.1),
rescale(d, add = 0.5),
ignore_attr = TRUE
)
expect_equal(
rescale(d, multiply = list(x = 1.1, y = 0.5)),
rescale(d, add = list(x = 0.5, y = -2.5)),
ignore_attr = TRUE
)
# data frames accept multiple add-values per column
out <- rescale(d, add = list(x = c(1, 3), y = c(2, 4)))
expect_equal(
out$x,
rescale(d$x, add = c(1, 3)),
ignore_attr = TRUE
)
expect_equal(
out$y,
rescale(d$y, add = c(2, 4)),
ignore_attr = TRUE
)

expect_error(rescale(d, multiply = 0.9, add = 1), regex = "Only one of")
expect_error(rescale(d, multiply = list(x = 0.9, y = 2), add = list(y = 1)), regex = "Only one of")
expect_error(rescale(d, multiply = c(0.9, 1.5)), regex = "The length of")
})

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