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

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Stepan Subik
Stepan Subik 2020-5-25
评论： Ameer Hamza 2020-5-29
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 个评论
Stepan Subik
Stepan Subik 2020-5-25
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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Ameer Hamza
Ameer Hamza 2020-5-25
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]);
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Ameer Hamza
Ameer Hamza 2020-5-29
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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