Visualize Distribution for an "optimal_bins" Object

Source: R/binning.R

It generates plots for understand distribution, frequency, bad rate, and weight of evidence using optimal_bins.

See vignette("transformation") for an introduction to these concepts.

# S3 method for optimal_bins
plot(
  x,
  type = c("all", "dist", "freq", "posrate", "WoE"),
  typographic = TRUE,
  base_family = NULL,
  rotate_angle = 0,
  ...
)

Arguments

x

an object of class "optimal_bins", usually, a result of a call to binning_by().

type

character. options for visualization. Distribution ("dist"), Relateive Frequency ("freq"), Positive Rate ("posrate"), and Weight of Evidence ("WoE"). and default "all" draw all plot.

typographic

logical. Whether to apply focuses on typographic elements to ggplot2 visualization. The default is TRUE. if TRUE provides a base theme that focuses on typographic elements using hrbrthemes package.

base_family

character. The name of the base font family to use for the visualization. If not specified, the font defined in dlookr is applied. (See details)

rotate_angle

integer. specifies the rotation angle of the x-axis label. This is useful when the x-axis labels are long and overlap. The default is 0 to not rotate the label.

...

further arguments to be passed from or to other methods.

Value

An object of gtable class.

Details

The base_family is selected from "Roboto Condensed", "Liberation Sans Narrow", "NanumSquare", "Noto Sans Korean". If you want to use a different font, use it after loading the Google font with import_google_font().

Examples

# Generate data for the example
heartfailure2 <- heartfailure
heartfailure2[sample(seq(NROW(heartfailure2)), 5), "creatinine"] <- NA

# optimal binning using binning_by()
bin <- binning_by(heartfailure2, "death_event", "creatinine")
#> Warning: The factor y has been changed to a numeric vector consisting of 0 and 1.
#> 'Yes' changed to 1 (positive) and 'No' changed to 0 (negative).

if (!is.null(bin)) {
  # visualize all information for optimal_bins class
  plot(bin)

  # rotate the x-axis labels by 45 degrees so that they do not overlap.
  plot(bin, rotate_angle = 45)

  # visualize WoE information for optimal_bins class
  plot(bin, type = "WoE")

  # visualize all information with typographic
  plot(bin)
}