#' Manual binning
#'
#' Bin continuous data manually.
#'
#' @param data A \code{data.frame} or \code{tibble}.
#' @param response Response variable.
#' @param predictor Predictor variable.
#' @param cut_points Cut points for binning.
#' @param include_na logical; if \code{TRUE}, a separate bin is created for missing values.
#' @param x An object of class \code{rbin_manual}.
#' @param print_plot logical; if \code{TRUE}, prints the plot else returns a plot object.
#' @param ... further arguments passed to or from other methods.
#'
#' @return A \code{tibble}.
#'
#' @details Specify the upper open interval for each bin. `rbin`
#' follows the left closed and right open interval. If you want to create_bins
#' 10 bins, the app will show you only 9 input boxes. The interval for the 10th bin
#' is automatically computed. For example, if you want the first bin to have all the
#' values between the minimum and including 36, then you will enter the value 37.
#'
#' @examples
#' bins <- rbin_manual(mbank, y, age, c(29, 31, 34, 36, 39, 42, 46, 51, 56))
#' bins
#'
#' # plot
#' plot(bins)
#'
#' @export
#'
rbin_manual <- function(data = NULL, response = NULL, predictor = NULL, cut_points = NULL, include_na = TRUE) UseMethod("rbin_manual")
#' @export
#'
rbin_manual.default <- function(data = NULL, response = NULL, predictor = NULL, cut_points = NULL, include_na = TRUE) {
resp <- deparse(substitute(response))
pred <- deparse(substitute(predictor))
var_names <- names(data[c(resp, pred)])
prep_data <- data[c(resp, pred)]
if (include_na) {
bm <- prep_data
} else {
bm <- na.omit(prep_data)
}
colnames(bm) <- c("response", "predictor")
bm$bin <- NA
byd <- bm$predictor
l_freq <- append(min(byd, na.rm = TRUE), cut_points)
u_freq <- c(cut_points, (max(byd, na.rm = TRUE) + 1))
bins <- length(cut_points) + 1
for (i in seq_len(bins)) {
bm$bin[bm$predictor >= l_freq[i] & bm$predictor < u_freq[i]] <- i
}
k <- bin_create(bm)
sym_sign <- c(rep("<", (bins - 1)), ">=")
fbin2 <- f_bin(u_freq)
intervals <- create_intervals(sym_sign, fbin2)
if (include_na) {
na_present <- nrow(k) > bins
if (na_present) {
intervals <- rbind(intervals, cut_point = 'NA')
}
}
result <- list(bins = cbind(intervals, k),
method = "Manual",
vars = var_names,
lower_cut = l_freq,
upper_cut = u_freq)
class(result) <- c("rbin_manual")
return(result)
}
#' @export
#'
print.rbin_manual <- function(x, ...) {
rbin_print(x)
cat("\n\n")
print(x$bins[c('cut_point', 'bin_count', 'good', 'bad', 'woe', 'iv', 'entropy')])
}
#' @rdname rbin_manual
#' @export
#'
plot.rbin_manual <- function(x, print_plot = TRUE, ...) {
p <- plot_bins(x)
if (print_plot) {
print(p)
}
invisible(p)
}
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