How to avoid creating lots of variables from calculation from a table

Hi All,

I am still a beginner at this...

I have a table of data (dataTable) that the code below sets up, the point being there is a variable name ('Var') and a suffix of 1 to 10 in this example. From 'dataTable' I want to calculate the mean of a defined section for each variable, and ends with compiling the results into one array.

Is there a way to do this without having to create all the separate variables meanVar1...meanVar10 as below from the dataTable? Thanks and much appreciated.

Time = [0;1;2;3;4;5;6;7;8;9;10];
Var1 = randi([-10 10],1,11)';
Var2 = randi([-10 10],1,11)';
Var3 = randi([-10 10],1,11)';
Var4 = randi([-10 10],1,11)';
Var5 = randi([-10 10],1,11)';
Var6 = randi([-10 10],1,11)';
Var7 = randi([-10 10],1,11)';
Var8 = randi([-10 10],1,11)';
Var9 = randi([-10 10],1,11)';
Var10 = randi([-10 10],1,11)';
dataTable = table(Time, Var1, Var2, Var3, Var4, Var5, Var6, Var7, Var8, Var9, Var10);

meanVar1 = mean(dataTable.Var1(3:7));
meanVar2 = mean(dataTable.Var2(3:7));
meanVar3 = mean(dataTable.Var3(3:7));
meanVar4 = mean(dataTable.Var4(3:7));
meanVar5 = mean(dataTable.Var5(3:7));
meanVar6 = mean(dataTable.Var6(3:7));
meanVar7 = mean(dataTable.Var7(3:7));
meanVar8 = mean(dataTable.Var8(3:7));
meanVar9 = mean(dataTable.Var9(3:7));
meanVar10 = mean(dataTable.Var10(3:7));

meanscompilation = [meanVar1;meanVar2;meanVar3;meanVar4;meanVar5;meanVar6;meanVar7;meanVar8;meanVar9;meanVar10];

Answer 1

[Steven Lord]

If all the variables you want to add to the table array are the same type, create one array and use array2table or (given that you have time data) perhaps array2timetable.

Time = [0;1;2;3;4;5;6;7;8;9;10];
VarData = randi([-10 10], 11, 10);
names = ["Time", "Var"+(1:10)];
dataTable = array2table([Time, VarData], 'VariableNames', names)

dataTable = 11×11 table
    Time    Var1    Var2    Var3    Var4    Var5    Var6    Var7    Var8    Var9    Var10
    ____    ____    ____    ____    ____    ____    ____    ____    ____    ____    _____

      0       3       6       4      -8      -7       5       8       1       0      -2  
      1      -6       2       4       0      10     -10      10     -10       2       1  
      2       3     -10       2       0      -6      -6       4      -4      -3      -5  
      3      -8       1      -5       0      -2       3      -4     -10      -9      -1  
      4     -10     -10      -6       7       7      10       7      -1       4      -3  
      5      -6       8      -5      -8     -10      -8      -9       9       3      -7  
      6       3      -3      -4     -10      -7       0      -3      -3       7      -5  
      7      -9       8      10       4      -9       2      -2      -6      -6      10  
      8       3      -7       8      -7      -4     -10      -9     -10      -7      -1  
      9      -3       9       6       8      -4      -6      -8       2      -3      -3  
     10       1      -9       7      -3      -3      -9       4       7       1       7  

Since your release predates the introduction of the ability to perform math on tables directly (release R2023a) I'd use varfun.

M = varfun(@mean, dataTable)

M = 1×11 table
    mean_Time    mean_Var1    mean_Var2    mean_Var3    mean_Var4    mean_Var5    mean_Var6    mean_Var7    mean_Var8    mean_Var9    mean_Var10
    _________    _________    _________    _________    _________    _________    _________    _________    _________    _________    __________

        5         -2.6364     -0.45455      1.9091       -1.5455      -3.1818      -2.6364     -0.18182      -2.2727        -1         -0.81818 

If upgrading to release R2023a or later is an option:

M23a = mean(dataTable)

M23a = 1×11 table
    Time     Var1        Var2       Var3      Var4       Var5       Var6        Var7       Var8      Var9     Var10  
    ____    _______    ________    ______    _______    _______    _______    ________    _______    ____    ________

     5      -2.6364    -0.45455    1.9091    -1.5455    -3.1818    -2.6364    -0.18182    -2.2727     -1     -0.81818

Note that both these approaches by default will also operate on the Time variable in dataTable. You could specify InputVariables when calling varfun to skip operating on Time.

M = varfun(@mean, dataTable, 'InputVariables', 2:width(dataTable))

M = 1×10 table
    mean_Var1    mean_Var2    mean_Var3    mean_Var4    mean_Var5    mean_Var6    mean_Var7    mean_Var8    mean_Var9    mean_Var10
    _________    _________    _________    _________    _________    _________    _________    _________    _________    __________

     -2.6364     -0.45455      1.9091       -1.5455      -3.1818      -2.6364     -0.18182      -2.2727        -1         -0.81818 

[Wah On Ho]

That's great thank you very much.

I did make a slight mod to your solutions to select a section of data from the middle of the table...

M = varfun(@mean, dataTable(3:7,:))

M = varfun(@mean, dataTable(3:7,:), 'InputVariables', 2:width(dataTable))