plot.optimal_bins {dlookr} | R Documentation |
Visualize Distribution for an "optimal_bins" Object
Description
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.
Usage
## S3 method for class '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. |
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().
Value
An object of gtable class.
See Also
binning_by
, summary.optimal_bins
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")
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)
}