Plot a scatter plot on a boxplot with two variables.

There are 4 related functions that use geom_point to plot a categorical variable along the X axis.

plot_point_sd (mean & SD, SEM or CI95 error bars)
plot_scatterbar_sd (bar & SD, SEM or CI95 error bars)
plot_scatterbox (box & whiskers)
plot_scatterviolin (box & whiskers, violin)

plot_scatterbox(
  data,
  xcol,
  ycol,
  facet,
  symsize = 3,
  s_alpha = 0.8,
  b_alpha = 1,
  bwid = 0.5,
  jitter = 0.1,
  TextXAngle = 0,
  LogYTrans,
  LogYBreaks = waiver(),
  Ylabels = waiver(),
  LogYLimits = NULL,
  facet_scales = "fixed",
  fontsize = 20,
  symthick,
  bthick,
  ColPal = c("okabe_ito", "all_grafify", "bright", "contrast", "dark", "fishy", "kelly",
    "light", "muted", "pale", "r4", "safe", "vibrant"),
  ColSeq = TRUE,
  ColRev = FALSE,
  SingleColour = "NULL",
  ...
)

Arguments

data: a data table object, e.g. data.frame or tibble.
xcol: name of the column to plot on X axis. This should be a categorical variable.
ycol: name of the column to plot on quantitative Y axis. This should be a quantitative variable.
facet: add another variable from the data table to create faceted graphs using ggplot2facet_wrap.
symsize: size of symbols, default set to 3.
s_alpha: fractional opacity of symbols, default set to 0.8 (i.e, 80% opacity).
b_alpha: fractional opacity of boxes, default set to 1.
bwid: width of boxplots; default 0.5.
jitter: extent of jitter (scatter) of symbols, default is 0.1.
TextXAngle: orientation of text on X-axis; default 0 degrees. Change to 45 or 90 to remove overlapping text.
LogYTrans: transform Y axis into "log10" or "log2"
LogYBreaks: argument for ggplot2[scale_y_continuous] for Y axis breaks on log scales, default is waiver(), or provide a vector of desired breaks.
Ylabels: argument for ggplot2[scale_y_continuous] for Y axis labels on log scales, default is waiver(), or provide a vector of desired labels.
LogYLimits: a vector of length two specifying the range (minimum and maximum) of the Y axis.
facet_scales: whether or not to fix scales on X & Y axes for all graphs. Can be fixed (default), free, free_y or free_x (for Y and X axis one at a time, respectively).
fontsize: parameter of base_size of fonts in theme_classic, default set to size 20.
symthick: size (in 'pt' units) of outline of symbol lines (stroke), default = fontsize/22.
bthick: thickness (in 'pt' units) of boxplot lines; default = fontsize/22.
ColPal: grafify colour palette to apply, default "okabe_ito"; see graf_palettes for available palettes.
ColSeq: logical TRUE or FALSE. Default TRUE for sequential colours from chosen palette. Set to FALSE for distant colours, which will be applied using scale_fill_grafify2.
ColRev: whether to reverse order of colour within the selected palette, default F (FALSE); can be set to T (TRUE).
SingleColour: a colour hexcode (starting with #), a number between 1-154, or names of colours from grafify or base R palettes to fill along X-axis aesthetic. Accepts any colour other than "black"; use grey_lin11, which is almost black.
...: any additional arguments to pass to ggplot2geom_boxplot.

Value

This function returns a ggplot2 object of class "gg" and "ggplot".

Details

These functions take a data table, categorical X and numeric Y variables, and plot various geometries. The X variable is mapped to the fill aesthetic of symbols.

In plot_point_sd and plot_scatterbar_sd, default error bars are SD, which can be changed to SEM or CI95.

Colours can be changed using ColPal, ColRev or ColSeq arguments. Colours available can be seen quickly with plot_grafify_palette. ColPal can be one of the following: "okabe_ito", "dark", "light", "bright", "pale", "vibrant, "muted" or "contrast". ColRev (logical TRUE/FALSE) decides whether colours are chosen from first-to-last or last-to-first from within the chosen palette. ColSeq decides whether colours are picked by respecting the order in the palette or the most distant ones using colorRampPalette.

If you prefer a single colour for the graph, use the SingleColour argument.

Examples

plot_scatterbox(data = data_cholesterol, 
xcol = Treatment, ycol = Cholesterol)


plot_scatterbox(data = data_doubling_time, 
xcol = Student, ycol = Doubling_time,
SingleColour = "ok_grey")