Make boxplots
boxwork( df, x, y, xs = defcx(), ys = defy(), fill = opts$boxplot.fill, alpha = opts$boxplot.alpha, hline = NULL, title = NULL, shown = TRUE, points = NULL, outlier.shape = opts$boxplot.outlier.shape, ... )
| df | data frame to plot |
|---|---|
| x | character name for x-axis data |
| y | character name for y-axis data |
| xs | see |
| ys | see |
| fill | passed to |
| alpha | passed to |
| hline | used to draw horizontal reference line |
| title | passed to |
| shown | if |
| points | show points in back of transparent boxes; if |
| outlier.shape | passed to |
| ... | arguments passed to |
Since this function creates a boxplot,
the x column must be character, factor
or logical and y column must
be numeric.
If shown is TRUE, a numeric summary of each
box is included
below each box. In the summary, n is the number of
non-NA observations in the y column for that box and
N is the number of unique ID values for
that box. An error will be generated if ID does
not exist in the plotting data frame when shown is
TRUE. When N is equal to n in the
summary, only n is shown.
The summaries will not be correct if the plot is eventually faceted by
another variable in the data set. In this case, either use
shown=FALSE or create the plot with split_plot.
When the user passes the points argument, outlier.shape is
automatically switched to NA so that outlier points are only plotted
once. The fill argument is also set to NA, so that boxes become
transparent, showing the points.
When the user sets points to TRUE, grey points are shown
in back of transparent boxes and the points are jittered in the x-direction.
The user can customize the display of the points by passing a list of
arguments for geom_point (for example, change the color, transparency,
size, jitter amount, etc).