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#' @title Expand (i.e. replicate rows) a data frame
#' @name data_replicate
#'
#' @description
#' Expand a data frame by replicating rows based on another variable that
#' contains the counts of replications per row.
#'
#' @param data A data frame.
#' @param expand The name of the column that contains the counts of replications
#' for each row. Can also be a numeric value, indicating the position of that
#' column. Note that the variable indicated by `expand` must be an integer vector.
#' @param remove_na Logical. If `TRUE`, missing values in the column
#' provided in `expand` are removed from the data frame. If `FALSE` and `expand`
#' contains missing values, the function will throw an error.
#' @param ... Currently not used.
#' @inheritParams extract_column_names
#'
#' @return A dataframe with each row replicated as many times as defined in `expand`.
#'
#' @examples
#' data(mtcars)
#' data_replicate(head(mtcars), "carb")
#' @export
data_replicate <- function(data,
expand = NULL,
select = NULL,
exclude = NULL,
remove_na = FALSE,
ignore_case = FALSE,
verbose = TRUE,
regex = FALSE,
...) {
# we need a name for the new column
if (is.null(expand)) {
insight::format_error(
"No column that should be used to expand the data frame was provided. Please use `expand` to define a column."
)
}
# only one column name
if (length(expand) > 1) {
insight::format_error(
"Please provide only a single string for `expand`, no character vector with multiple values."
)
}
# check if numerics, and if so, use column name
if (is.numeric(expand)) {
expand <- colnames(data)[expand]
}
# check if in data
if (!expand %in% colnames(data)) {
insight::format_error(
"The column provided in `expand` does not exist in the data frame.",
.misspelled_string(colnames(data), expand, "Possibly misspelled?")
)
}
# check that "expand" contains no Inf
if (any(is.infinite(data[[expand]]))) {
insight::format_error(
"The column provided in `expand` contains infinite values. Please provide a column that does not contain infinite values." # nolint
)
}
# check that "expand" is integer
if (!.is_integer(data[[expand]])) {
insight::format_error(
"The column provided in `expand` is not of type integer. Please provide a column that contains integer values." # nolint
)
}
# evaluate select/exclude, may be select-helpers
select <- .select_nse(select,
data,
exclude,
ignore_case,
regex = regex,
verbose = verbose
)
# extract variable that contains the counts of replicates
replicates <- data[[expand]]
# we can remove that column now
data[[expand]] <- NULL
# also remove "expand" from "select" string
select <- setdiff(select, expand)
# if user doesn't want to remove "NA", but replicates contain "NA",
# give informative error here
if (!remove_na && anyNA(replicates)) {
insight::format_error(
"The column provided in `expand` contains missing values, but `remove_na` is set to `FALSE`.",
"Please set `remove_na` to `TRUE` or remove the missing values from the `expand` variable."
)
}
# remove rows where "expand" is NA
data <- data[!is.na(replicates), ]
replicates <- replicates[!is.na(replicates)]
# fin
as.data.frame(do.call(cbind, lapply(data[select], rep.int, times = replicates)))
}
# is.integer(c(1, 2)) -> FALSE
# all(c(1, 2) %% 1 == 0) -> TRUE
.is_integer <- function(x, remove_na = TRUE) {
if (remove_na) {
x <- x[!is.na(x)]
}
tryCatch(
all(x %% 1 == 0),
warning = function(w) is.integer(x),
error = function(e) FALSE
)
}
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