This function takes a data table, categorical X and numeric Y variables, and plots a point showing the mean with SD error bars as default (SEM & CI95 are other options). The X variable is mapped to the
fill aesthetic of symbols.
plot_point_sd( data, xcol, ycol, facet, ErrorType = "SD", symsize = 3.5, s_alpha = 1, symshape = 21, all_alpha = 0, all_size = 2.5, all_shape = 1, all_jitter = 0, ewid = 0.2, TextXAngle = 0, LogYTrans, LogYBreaks = waiver(), LogYLabels = waiver(), LogYLimits = NULL, facet_scales = "fixed", fontsize = 20, symthick, ethick, ColPal = c("okabe_ito", "all_grafify", "bright", "contrast", "dark", "fishy", "kelly", "light", "muted", "pale", "r4", "safe", "vibrant"), ColSeq = TRUE, ColRev = FALSE, SingleColour = "NULL", ... )
a data table object, e.g. data.frame or tibble.
name of the column with a categorical X variable.
name of the column with quantitative Y variable.
add another variable from the data table to create faceted graphs using
select the type of error bars to display. Default is "SD" (standard deviation). Other options are "SEM" (standard error of the mean) and "CI95" (95% confidence interval based on t distributions).
size of point symbols, default set to 3.5.
fractional opacity of symbols, default set to 1 (i.e. maximum opacity & zero transparency).
The mean is shown with symbol of the shape number 21 (default, filled circle). Pick a number between 0-25 to pick a different type of symbol from ggplot2.
fractional opacity of all data points (default = 0; i.e., not shown). Set to non-zero value if you would like all data points plotted in addition to the mean.
size of symbols of all data points, if shown (default = 2.5).
all data points are shown with symbols of the shape number 1 (default, transparent circle). Pick a number between 0-25 to pick a different type of symbol from ggplot2.
reduce overlap of all data points, if shown, by setting a value between 0-1 (default = 0).
width of error bars, default set to 0.2.
orientation of text on X-axis; default 0 degrees. Change to 45 or 90 to remove overlapping text.
transform Y axis into "log10" or "log2"
ggplot2[scale_y_continuous] for Y axis breaks on log scales, default is
waiver(), or provide a vector of desired breaks.
ggplot2[scale_y_continuous] for Y axis labels on log scales, default is
waiver(), or provide a vector of desired labels.
a vector of length two specifying the range (minimum and maximum) of the Y axis.
whether or not to fix scales on X & Y axes for all facet facet graphs. Can be
free_x (for Y and X axis one at a time, respectively).
base_size of fonts in
theme_classic, default set to size 20.
thickness of symbol border, default set to
thickness of error bar lines; default
grafify colour palette to apply, default "okabe_ito"; see
graf_palettes for available palettes.
logical TRUE or FALSE. Default TRUE for sequential colours from chosen palette. Set to FALSE for distant colours, which will be applied using
whether to reverse order of colour within the selected palette, default F (FALSE); can be set to T (TRUE).
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
This function returns a
ggplot2 object of class "gg" and "ggplot".
The function uses
geom = "point" with
size = 3.
Standard deviation (SD) is plotted through
stat_summary calculated using
mean_sdl from the
ggplot2 package (get help with
?mean_sdl), and 1x SD is plotted (
fun.arg = list(mult = 1).
mean_cl_normal are used for SEM and CI95, respectively.
Colours can be changed using
ColSeq arguments. Colours available can be seen quickly with
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 (logical TRUE/FALSE) decides whether colours are picked by respecting the order in the palette or the most distant ones using
If there are many groups along the X axis and you prefer a single colour for the graph,use the
You are instead encouraged to show all data using the following functions:
#Basic usage plot_point_sd(data = data_doubling_time, xcol = Student, ycol = Doubling_time) #show all data points plot_point_sd(data = data_2w_Tdeath, xcol = Genotype, ycol = PI, facet = Time, all_alpha = 0.4)