This function takes a data table, ycol of quantitative variable and a categorical grouping variable (group), if available, and plots a density graph using geom_density).

plot_density(
data,
ycol,
group,
facet,
c_alpha = 0.2,
TextXAngle = 0,
facet_scales = "fixed",
fontsize = 20,
linethick,
Group,
alpha,
ColPal = c("okabe_ito", "all_grafify", "bright", "contrast", "dark", "fishy", "kelly",
"light", "muted", "pale", "r4", "safe", "vibrant"),
ColSeq = TRUE,
ColRev = FALSE,
...
)

Arguments

data

a data table e.g. data.frame or tibble.

ycol

name of the column containing the quantitative variable whose density distribution is to be plotted.

group

name of the column containing a categorical grouping variable

facet

add another variable from the data table to create faceted graphs using ggplot2facet_wrap.

c_alpha

fractional opacity of filled colours under the curve, default set to 0.2 (i.e. 20% opacity).

TextXAngle

orientation of text on X-axis; default 0 degrees. Change to 45 or 90 to remove overlapping text.

facet_scales

whether or not to fix scales on X & Y axes for all facet facet 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.

linethick

thickness of symbol border, default set to fontsize/22.

Group

deprecated old argument for group; retained for backward compatibility.

alpha

deprecated old argument for c_alpha; retained for backward compatibility.

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).

...

any additional arguments to pass to ggplot2geom_density.

Value

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

Details

Note that the function requires the quantitative Y variable first, and groups them based on an X variable. The group variable is mapped to the fill and colour aesthetics in geom_density. 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.

Examples

plot_density(data = data_t_pratio,
ycol = log(Cytokine), group = Genotype)
#> Warning: The following aesthetics were dropped during statistical transformation: sample
#> ℹ This can happen when ggplot fails to infer the correct grouping structure in
#>   the data.
#> ℹ Did you forget to specify a group aesthetic or to convert a numerical
#>   variable into a factor?

#with faceting
plot_density(data = data_cholesterol,
ycol = Cholesterol, group = Treatment,
fontsize = 10)+facet_wrap("Treatment")
#> Warning: The following aesthetics were dropped during statistical transformation: sample
#> ℹ This can happen when ggplot fails to infer the correct grouping structure in
#>   the data.
#> ℹ Did you forget to specify a group aesthetic or to convert a numerical
#>   variable into a factor?
#> Warning: The following aesthetics were dropped during statistical transformation: sample
#> ℹ This can happen when ggplot fails to infer the correct grouping structure in
#>   the data.
#> ℹ Did you forget to specify a group aesthetic or to convert a numerical
#>   variable into a factor?