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Is it possible to visualize all data in a multiple scatterplot?

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Hi,
I am trying to make a scatterplot with a lots of data via this code:
h1 = scatter(table{:,variable},table{:,'PET'}, '+','MarkerEdgeColor',[102/255, 178/255, 255/255]);
hold on
h2 = scatter(table{:,variable},table{:,'SET_'}, '+','MarkerEdgeColor',[102/255, 255/255, 102/255]);
h3 = scatter(table{:,variable},table{:,'UTCI'}, '+','MarkerEdgeColor',[255/255, 204/255, 153/255]);
h4 = scatter(table{:,variable},table{:,'PT'}, '+','MarkerEdgeColor',[255/255, 102/255, 102/255]);
h5 = scatter(table{:,variable},table{:,'mPET'}, '+','MarkerEdgeColor',[204/255, 153/255, 255/255]);
and the result is this:
It is obvious that the last plotted violet data will be above the others hiding the other colors. Is it possible to visualize all data to the same extend? For example it can be plotted through a rotation of all colours to achieve the desired visibility of all the data.
  2 Comments
Stepan Subik
Stepan Subik on 25 May 2020
Hi, thank you for your suggestion. Unfortunatelly, this does not work in my case since I have too many data and the plot does not change with varying transparency.

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Accepted Answer

Ameer Hamza
Ameer Hamza on 25 May 2020
Maybe use scatter3() and visualize by using a z-offset. Not sure if it helps in your case
h1 = scatter3(table{:,variable},table{:,'PET'}, 0*ones(size(table{:,'PET'})), '+','MarkerEdgeColor',[102/255, 178/255, 255/255]);
hold on
h2 = scatter3(table{:,variable},table{:,'SET_'}, 1*ones(size(table{:,'SET_'})), '+','MarkerEdgeColor',[102/255, 255/255, 102/255]);
h3 = scatter3(table{:,variable},table{:,'UTCI'}, 2*ones(size(table{:,'UTCI'})), '+','MarkerEdgeColor',[255/255, 204/255, 153/255]);
h4 = scatter3(table{:,variable},table{:,'PT'}, 3*ones(size(table{:,'PT'})), '+','MarkerEdgeColor',[255/255, 102/255, 102/255]);
h5 = scatter3(table{:,variable},table{:,'mPET'}, 4*ones(size(table{:,'mPET'})), '+','MarkerEdgeColor',[204/255, 153/255, 255/255]);
  5 Comments
Ameer Hamza
Ameer Hamza on 29 May 2020
I am glad to be of help! Can you show the final figure and how it improved the visualization of all the points?

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