how to plot each bin of data individually?
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I am having the follwoing issues:
I have a table with three variables: time in hours, altitude and solar activity, according to a time interval of 3hrs I have divided my data into 8 bins using the function discretize.
How can we plot the data within each bin indiviually, i.e we have 8 bins we would like to have a graph for each bin, that is for each interval of time, so at the end we get 8 graphs.
in the plot the data of each row sholud be presented for ex by a dot.
attached is a text file containing a sample of the data I am working with.
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dpb
el 17 de Oct. de 2021
As per usual, would be easier to demonstrate with some real data to work with...but
tD=table(repmat([0:23].',4,1),randi([150 200]*1000,96,1),randi([10 70],96,1),'VariableNames',{'Hours','Altitude','Activity'});
tD.Bin=discretize(tD.Hours,8);
splitapply(@(x,y) plot(x,y,'*'),tD.Altitude,tD.Activity,tD.Bin)
xlabel('Altitude, ft')
ylabel('Activity, units')
tCenter=[1.5:3:24]; % bin time centers 0-3, 3-6, 6-9, ...
legend(compose('Time Bin %4.1f hrs',tCenter.')) % label by the group time centers
might be a fair starting point...
3 comentarios
dpb
el 18 de Oct. de 2021
I'm sure there is, but what, specifically, do you mean? The above is for each bin.
Más respuestas (2)
dpb
el 18 de Oct. de 2021
OK, here's another example; I'll add it as its own Answer -- carrying on from the above
uBin=unique(tD.Bin);
for i=uBin(:).'
nexttile
isBin=(tD.Bin==i);
scatter(tD.NE8(isBin),tD.GDALT(isBin),'.')
legend("Bin "+i,'Location','best')
xlabel('NE, units'),ylabel('GDALT, ft')
box on
end
Steven Lord
el 18 de Oct. de 2021
Can you tell us which of the thumbnail pictures for the plotting functions included in MATLAB look closest to what you want to plot? If none of them do and you have other MathWorks toolboxes installed, open the Plots tab on the Toolstrip and see if any of the functions from a toolbox have thumbnails that look closer (maybe a boxplot from Statistics and Machine Learning Toolbox?)
6 comentarios
dpb
el 18 de Oct. de 2021
It's easy to overthink a problem, indeed... :)
Glad to help.
Investigate rowfun and friends if you do other analyses on these data by the grouping variable(s) -- extremely powerful construct for such purposes.
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