The list of the Unicode characters that can be applied to the plotting symbols in R Widget can be found here: https://www.alanwood.net/unicode/miscellaneous_symbols.html
The pumpkin raster graphic that will be used in one of the charts originates from this source: https://iconarchive.com
The data that is depicted in that chart can be found here: https://de.statista.com/statistik/daten/studie/640501/umfrage/erntemenge-von-speisekuerbissen-in-deutschland/
Below you can see the standard scatterplot that depicts the dependency of the pressure applied on the container walls as a result of heating up (temperature) the explosive substance inside of the container:
Indeed, Halloween is not Halloween without a pumpkin somewhere in between! :-)
And this can actually be achieved within the SAC R Widget as well.
Though, this time I would prefer a complex raster image as the plotting symbol as opposed to the fancy Unicode character.
For this purpose I have downloaded the pumpkin PNG icon from the source given in the introduction side panel above.
It's important to translate this PNG into the matrix of the hexadecimal values all starting with the '#' symbol as seen in the source code below:
One can basically discern that single raster pixels are now represented as a matrix of characters all starting with the '#' symbol as is convenient for the R representation of the hexadecimal values.
Each of these hexadecimal values is in fact a value for the color of that particular pixel.
This matrix is subsequently assigned to the 'icon' variable.
One can easily do this kind of transformation of the raster picture into the character matrix using i.e. on-line conversion tools or terminal conversion routines, including the desktop R engine itself using as.raster() and rasterImage() functions. ;-)
To find out more, simply search the documentation on the internet for those commands.
The code snippet below shows how this character matrix of hexadecimal values (icon) is read into a variable (icon2) and used as a plotting symbol within the rasterImage() function:
Below is the result of that source code:
The underlying data for the harvest volume in tones recorded for a particular year in Germany are taken from the source mentioned in the introduction side panel and look as follows: