Problem plotting 1D array versus table column: I want a single curve/series but am instead getting a separate series for every array element.

I have used Matlab's "Import Data" facility to import a single column of data from a file. I can plot it by doing this:

plot(myTable.TotalMt)

However, because each element in the imported data represents half a time step, the x axis in the plot is twice as long as I want it to be.

My solution is to create an array called "time" like this:

timeLimit=(size(myTable.TotalMt));
time=1:timeLimit;
time = time./2;

And then plot that with the imported data plus a line representing the average of the imported data:

plot(time,myTable.TotalMt); hold on
mean_simple = mean(myTable.TotalMt,1);
plot(time,mean_simple);

There's a problem though. I have over 200000 series in the plot. It seems that each row of the array and imported table column is being plotted as a separate series. I'm not that experienced in Matlab and if anyone has advice on how to do this the right way, I would be grateful.

Answer 1

[Seth Furman]

I'd first recommend converting your table into a timetable so you can see the time step for each row.

https://www.mathworks.com/help/matlab/ref/table2timetable.html

For example,

>> t = table2timetable(table((1:10)'),'SampleRate',2)

t =

  10×1 timetable

     Time      Var1
    _______    ____

    0 sec        1 
    0.5 sec      2 
    1 sec        3 
    1.5 sec      4 
    2 sec        5 
    2.5 sec      6 
    3 sec        7 
    3.5 sec      8 
    4 sec        9 
    4.5 sec     10 

You can then plot your data directly using stackedplot.

https://www.mathworks.com/help/matlab/ref/stackedplot.html

stackedplot(t)

It sounds like myTable.TotalMt has multiple columns. By default the plot and stackedplot functions will plot these separate columns as multiple lines. To plot a single column of a table variable you can split that column into multiple variables with splitvars.

For example,

>> t = timetable([(1:10)' (2:11)'],'SampleRate',2)

t =

  10×1 timetable

     Time        Var1  
    _______    ________

    0 sec       1     2
    0.5 sec     2     3
    1 sec       3     4
    1.5 sec     4     5
    2 sec       5     6
    2.5 sec     6     7
    3 sec       7     8
    3.5 sec     8     9
    4 sec       9    10
    4.5 sec    10    11

>> t = splitvars(t,'Var1')

t =

  10×2 timetable

     Time      Var1_1    Var1_2
    _______    ______    ______

    0 sec         1         2  
    0.5 sec       2         3  
    1 sec         3         4  
    1.5 sec       4         5  
    2 sec         5         6  
    2.5 sec       6         7  
    3 sec         7         8  
    3.5 sec       8         9  
    4 sec         9        10  
    4.5 sec      10        11  

>> stackedplot(t,"Var1_1")