I want to know if it is possible to represent with different colours in a scatter plot more than 10 parameters instead of putting others and assigning a colour if the number of parameters overpasses 10. I was following the instructions on the web but the discrete variables are not working. I used the colour icon and I assigned colours to all my discrete variables, but when I sent this information to the scatter plot it didn't work. The program puts random colours ignoring the ones that I selected. I don´t know if there is any trick to make it work. Is there any method to apply to represent 160 parameters each one with its own color?
Is there any option to represent 160 discrete variables each one with their own color in scatter plot?
2$\begingroup$ You can do it but the question is more are you going to be able to distinguish the 160 colors from each others ? If you tell use what those 160 variables represent maybe we can help you to find a good way to vizualize them. $\endgroup$– Robin NicoleApr 23, 2019 at 10:38
1$\begingroup$ Welcome to this site. At this point it might be a good question ot ask yourself if you can introduce some meaning in the colours. Would it make sense to map the 160 colors into the RGB color triangle? You could also use contrast and saturation as a scale too. Mapping them e.g. on a color wheel gives you even further possibilities. Just search for the meaning of the 160 values/symbols that you have. $\endgroup$– maptoApr 23, 2019 at 11:12
1$\begingroup$ What program are you trying with? $\endgroup$– maptoApr 23, 2019 at 11:26
$\begingroup$ What information are you trying to communicate and how is your data shaped? A sample of the data would be good. Also, some code of what you have tried thus far. $\endgroup$– EdmundApr 23, 2019 at 21:03
The number of colours you can use in a scatter plot will vary depending on what software or programming language you are using.
The main issue is that scatter plots might not be the best option to use if you want to distinguish 160 different variables, particularly if you are only distinguishing them by colour.
If you can group the variables you might be able to make it work with less colours, or consider using a different type of graph.
Do the colors mean something? Do you want to distinguish between all of them or there are groups between them?
This is my suggestion: Use the combination of color/shape to distinguish them in different ways, but first check if you can do any grouping which can easen your task.