funq_plot: Functional quantile plot

In qbinplots: Quantile Binned Plots

Functional quantile plot

Description

funq_plot() conditions on variable x with quantile binning and plots the median and interquartile range of numerical variables and level frequency of the other variables as a function the x variable.

Usage

funq_plot(
  data,
  x = NULL,
  n = 100,
  min_bin_size = NULL,
  overlap = NULL,
  color = "#002f2f",
  fill = "#2f4f4f",
  auto_fill = TRUE,
  ncols = NULL,
  xmarker = NULL,
  qmarker = NULL,
  show_bins = FALSE,
  xlim = NULL,
  connect = TRUE,
  ...
)

Arguments

data	a data.frame to be binned
x	character variable name used for the quantile binning
n	integer number of quantile bins.
min_bin_size	integer minimum number of rows/data points that should be in a quantile bin. If NULL it is initially sqrt(nrow(data))
overlap	logical if TRUE the quantile bins will overlap. Default value will be FALSE.
color	The color to use for the line charts
fill	The fill color to use for the areas
auto_fill	If TRUE, use a different color for each category
ncols	The number of column to be used in the layout
xmarker	numeric, the x marker.
qmarker	numeric, the quantile marker to use that is translated in a x value.
show_bins	if TRUE a rug is added to the plot
xlim	numeric, the limits of the x-axis.
connect	if TRUE subsequent medians are connected.
...	Additional arguments to pass to the plot functions

Details

By highlighting and connecting the median values it creates a functional view of the data. What is the (expected) median given a certain value of x?

It qbins the x variable and plots the medians of the qbins vs the other variables, thereby creating a functional view of x to the rest of the data, calculating the statistics for each bin, hence the name funq_plot.

Value

A ggplot object with the plots

See Also

Other conditional quantile plotting functions: cond_barplot(), cond_boxplot(), cond_heatmap()

Examples

funq_plot(iris, "Sepal.Length", xmarker=5.5)



  funq_plot(
    iris,
    x = "Sepal.Length",
    xmarker=5.5,
    overlap = TRUE
  )


  data("diamonds", package="ggplot2")
  funq_plot(diamonds[1:7], "carat", xlim=c(0,2))

  if (require(palmerpenguins)){
    funq_plot(
      penguins[1:7],
      x = "body_mass_g",
      xmarker=4650,
      ncol = 3
    )
  }

qbinplots documentation built on April 3, 2025, 6:33 p.m.