Error using extractAfter Numeric value exceeds the number of characters in element 1. What is wrong? How do I fix this?

I am trying to eliminate redundant variables from my excel sheet but when I have less than 14 variables I get this error:

Error using extractAfter

Numeric value exceeds the number of characters in element 1.

la(i) = extractAfter(ABAP1(i,1),2)+"^"+extractBetween(ABAP1(i,1),2,2)+"_"+ABAP1(i,2);

%% Set up the Import Options and import the data
opts = spreadsheetImportOptions("NumVariables", 13);
% Specify sheet and range
opts.Sheet = "Sheet2";
opts.DataRange = "A2:M73";
% Specify column names and types
opts.VariableNames = ["Type", "Slice", "Count", "Sphericity", "AvgFeret", "skewness", "kurtosis", "density", "normalizedArea", "totalArea", "avgSize", "zoneArea", "AvgMinFeret"]; %"VarName14", "VarName15", "VarName16", "VarName17", "VarName18", "VarName19"];
opts.VariableTypes = ["string", "string", "string", "string", "string", "string", "string", "string", "string", "string", "string", "string", "string"]; % "string", "string", "string", "string", "string", "string"];
% Specify variable propertie
opts = setvaropts(opts, ["Type", "Slice", "Count", "Sphericity", "AvgFeret", "skewness", "kurtosis", "density", "normalizedArea", "totalArea", "avgSize", "zoneArea", "AvgMinFeret"], "WhitespaceRule", "preserve");
opts = setvaropts(opts, ["Type", "Slice", "Count", "Sphericity", "AvgFeret", "skewness", "kurtosis", "density", "normalizedArea", "totalArea", "avgSize", "zoneArea", "AvgMinFeret"], "EmptyFieldRule", "auto");
% Import the data
ABAP1 = readmatrix("excelname.xlsx", opts, "UseExcel", false);
ggmin=1;
ggmax=12;
gg=ggmin:ggmax;
per = 5;
%--------------------------------------
sz = size(ABAP1);
nObs = sz(1);
nVars = sz(2) - 3;
labels = cell(nObs, 1);
for i = 1:nObs
    labels{i} = ABAP1(i, 3); % Assuming C2 corresponds to the Type column
end
C = zeros(nObs,nVars);
co = ABAP1(:,1)+"_"+ABAP1(:,2);
coo = ABAP1(:,2);
for i = 1:nObs
    
    for j = 1:nVars
        seg(i) = str2double(ABAP1(i,3));
        seg2(i) = str2double(extractBetween(co(i),2,2));
        la(i) = extractAfter(ABAP1(i,1),2)+"^"+extractBetween(ABAP1(i,1),2,2)+"_"+ABAP1(i,2);
        lb(i) = extractAfter(ABAP1(i,1),2)+"_"+ABAP1(i,2);
        
        C(i,:) = str2double(ABAP1(i,4:nVars + 3));
        
    end
    % Assign label based on C, W, or E
    if ABAP1(i, end) == 'C'
        labels{i} = 'C';
    elseif ABAP1(i, end) == 'W'
        labels{i} = 'W';
    elseif ABAP1(i, end) == 'E'
        labels{i} = 'E';
    end
end

[Image Analyst]

If you have any more questions, then attach your workbook with the paperclip icon after you read this:

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[Chanille]

@Image Analyst I uploaded it.

[Chanille]

@Image Analyst I uploaded my datasheet.

   for j = 1:nVars
        seg(i) = str2double(ABAP1(i,3));
        seg2(i) = str2double(extractBetween(co(i),2,2));
        la(i) = extractAfter(ABAP1(i,1),2)+"^"+extractBetween(ABAP1(i,1),2,2)+"_"+ABAP1(i,2);
        lb(i) = extractAfter(ABAP1(i,1),2)+"_"+ABAP1(i,2);
        
        C(i,:) = str2double(ABAP1(i,4:nVars + 3));
        
    end

What does this snippet mean? I understand that there's alot of extracting and turning to a string but why is my question specifically for which step and why does the la line give error when i remove a column? Specifically what happens when I have to change the numbers in each line?

Answer 1

[Star Strider]

You are making this much too difficult!

If you want to remove specific variables, first use readmatrix (introduced in R2013b), and then removevars (introduced in R2018a). You are using readmatrix (introduced in R2019a), so you should have all of these functions.

T1 = readtable('exceldata.xlsx')

T1 = 216×12 table
    Slice    Count    Sphericity    AvgFeret    skewness    kurtosis     density      normalizedArea    totalArea    avgSize     zoneArea     AvgMinFeret
    _____    _____    __________    ________    ________    ________    __________    ______________    _________    _______    __________    ___________

      1      1063      0.47472       16.923      1.4261      6.3692      0.0006312        4.4013          74122      69.729     1.6841e+06      8.4711   
      2      1169      0.49888       15.938      0.7888      3.3704      0.0013679          8.76          74861      64.038     8.5458e+05       7.909   
      3       810      0.51745       14.838     0.62505      2.9444      0.0016288        10.552          52477      64.786      4.973e+05      7.7483   
      4       557       0.5335       15.268      0.3516      2.3852      0.0015122         10.24          37717      67.715     3.6833e+05      8.2089   
      5       550      0.54636       14.891     0.50214      2.6001      0.0015251        11.005          39687      72.158     3.6062e+05       8.135   
      6       447      0.54469       14.848     0.42885      2.3657      0.0012531        8.7629          31259      69.931     3.5672e+05      8.1118   
      7       543      0.53521       14.944     0.70428      2.8828      0.0015328        10.322          36565      67.339     3.5425e+05       8.083   
      8       578      0.53658       14.326     0.49199      2.4976      0.0016393        10.908          38461      66.542      3.526e+05      7.8097   
      9       648      0.53308       14.366     0.53685       2.512      0.0018443        12.542          44066      68.003     3.5135e+05      7.6789   
     10       658      0.51807       14.793     0.57635      2.3995      0.0018771        13.502          47329      71.929     3.5053e+05      7.8666   
     11       718      0.55385       13.675     0.40135      2.2474      0.0020526        12.903          45135      62.862      3.498e+05      7.1793   
     12       567      0.53844       14.657     0.44447      2.1955      0.0016232        11.361          39686      69.993     3.4932e+05      7.4717   
      1      1588      0.49734       15.452      1.0599      4.6982     0.00084496        5.2795          99223      62.483     1.8794e+06      7.7226   
      2      1126      0.50017       14.493     0.73674      2.9948      0.0017807         9.962          62994      55.945     6.3234e+05      7.2165   
      3       661      0.52046       15.027     0.60794      2.6089      0.0013816        8.5906          41100      62.179     4.7843e+05      7.7519   
      4       662      0.55396       13.591     0.65171      2.4891      0.0014232        8.1271          37803      57.104     4.6515e+05      7.3935   

See the removevars documentation for details on how to use the function.

.

[Chanille]

@Star Strider Since I am not an advanced coder I am trying not to change the code much. Wouldn't it be easier to explain how to change the string snippet to accomodate the change in variables (i.e. the variables removed)?

Otherwise how would I update the provided snippet to be much easier?

Thank you @Star Strider.

[Star Strider]

My pleasure!

The code you posted is very difficult for me to follow.

Please explain what you want to do.

[Chanille]

@Star Strider In the original exceldata I had an extra column that was useless so I removed it (i.e. in the provided excel it is not there) but now the following snippet:

for j = 1:nVars
    seg(i) = str2double(ABAP1(i,3));
    seg2(i) = str2double(extractBetween(co(i),2,2));
    la(i) = extractAfter(ABAP1(i,1),2)+"^"+extractBetween(ABAP1(i,1),2,2)+"_"+ABAP1(i,2);
    lb(i) = extractAfter(ABAP1(i,1),2)+"_"+ABAP1(i,2);
    
    C(i,:) = str2double(ABAP1(i,4:nVars + 3));
    
end

Does not work and it gives the above error. I changed it to this:

for j = 1:nVars
    seg(i) = str2double(ABAP1(i,2));
    seg2(i) = str2double(extractBetween(co(i),1,1));
    la(i) = extractAfter(ABAP1(i,1),1)+"^"+extractBetween(ABAP1(i,1),1,1)+"_"+ABAP1(i,1);
    lb(i) = extractAfter(ABAP1(i,1),1)+"_"+ABAP1(i,1);
    
    C(i,:) = str2double(ABAP1(i,3:nVars + 2));
    
end

And it now seems to be working but I would like to udnerstand why and if it is correctly assigning based on the provided excel sheet. Can you explain this?

[Star Strider]

Please explain what you want to do.

I do not see any "^" or "_" in any of the variable names.

Looking at the values in the table, it would appear that you might want to create a new matrices with different ‘pages’.

Example —

T1  = readtable('exceldata.xlsx')

T1 = 216×12 table
    Slice    Count    Sphericity    AvgFeret    skewness    kurtosis     density      normalizedArea    totalArea    avgSize     zoneArea     AvgMinFeret
    _____    _____    __________    ________    ________    ________    __________    ______________    _________    _______    __________    ___________

      1      1063      0.47472       16.923      1.4261      6.3692      0.0006312        4.4013          74122      69.729     1.6841e+06      8.4711   
      2      1169      0.49888       15.938      0.7888      3.3704      0.0013679          8.76          74861      64.038     8.5458e+05       7.909   
      3       810      0.51745       14.838     0.62505      2.9444      0.0016288        10.552          52477      64.786      4.973e+05      7.7483   
      4       557       0.5335       15.268      0.3516      2.3852      0.0015122         10.24          37717      67.715     3.6833e+05      8.2089   
      5       550      0.54636       14.891     0.50214      2.6001      0.0015251        11.005          39687      72.158     3.6062e+05       8.135   
      6       447      0.54469       14.848     0.42885      2.3657      0.0012531        8.7629          31259      69.931     3.5672e+05      8.1118   
      7       543      0.53521       14.944     0.70428      2.8828      0.0015328        10.322          36565      67.339     3.5425e+05       8.083   
      8       578      0.53658       14.326     0.49199      2.4976      0.0016393        10.908          38461      66.542      3.526e+05      7.8097   
      9       648      0.53308       14.366     0.53685       2.512      0.0018443        12.542          44066      68.003     3.5135e+05      7.6789   
     10       658      0.51807       14.793     0.57635      2.3995      0.0018771        13.502          47329      71.929     3.5053e+05      7.8666   
     11       718      0.55385       13.675     0.40135      2.2474      0.0020526        12.903          45135      62.862      3.498e+05      7.1793   
     12       567      0.53844       14.657     0.44447      2.1955      0.0016232        11.361          39686      69.993     3.4932e+05      7.4717   
      1      1588      0.49734       15.452      1.0599      4.6982     0.00084496        5.2795          99223      62.483     1.8794e+06      7.7226   
      2      1126      0.50017       14.493     0.73674      2.9948      0.0017807         9.962          62994      55.945     6.3234e+05      7.2165   
      3       661      0.52046       15.027     0.60794      2.6089      0.0013816        8.5906          41100      62.179     4.7843e+05      7.7519   
      4       662      0.55396       13.591     0.65171      2.4891      0.0014232        8.1271          37803      57.104     4.6515e+05      7.3935   

format shortE
M1 = table2array(T1);

M2 = reshape(M1, 12, [], 12);
M2 = permute(M2,[1 3 2]);

M2(:,:,1)

ans = 12×12

1.0e+00 * 1.0000e+00 1.0630e+03 4.7472e-01 1.6923e+01 1.4261e+00 6.3692e+00 6.3120e-04 4.4013e+00 7.4122e+04 6.9729e+01 1.6841e+06 8.4711e+00 2.0000e+00 1.1690e+03 4.9888e-01 1.5938e+01 7.8880e-01 3.3704e+00 1.3679e-03 8.7600e+00 7.4861e+04 6.4038e+01 8.5458e+05 7.9090e+00 3.0000e+00 8.1000e+02 5.1745e-01 1.4838e+01 6.2505e-01 2.9444e+00 1.6288e-03 1.0552e+01 5.2477e+04 6.4786e+01 4.9730e+05 7.7483e+00 4.0000e+00 5.5700e+02 5.3350e-01 1.5268e+01 3.5160e-01 2.3852e+00 1.5122e-03 1.0240e+01 3.7717e+04 6.7715e+01 3.6833e+05 8.2089e+00 5.0000e+00 5.5000e+02 5.4636e-01 1.4891e+01 5.0214e-01 2.6001e+00 1.5251e-03 1.1005e+01 3.9687e+04 7.2158e+01 3.6062e+05 8.1350e+00 6.0000e+00 4.4700e+02 5.4469e-01 1.4848e+01 4.2885e-01 2.3657e+00 1.2531e-03 8.7629e+00 3.1259e+04 6.9931e+01 3.5672e+05 8.1118e+00 7.0000e+00 5.4300e+02 5.3521e-01 1.4944e+01 7.0428e-01 2.8828e+00 1.5328e-03 1.0322e+01 3.6565e+04 6.7339e+01 3.5425e+05 8.0830e+00 8.0000e+00 5.7800e+02 5.3658e-01 1.4326e+01 4.9199e-01 2.4976e+00 1.6393e-03 1.0908e+01 3.8461e+04 6.6542e+01 3.5260e+05 7.8097e+00 9.0000e+00 6.4800e+02 5.3308e-01 1.4366e+01 5.3685e-01 2.5120e+00 1.8443e-03 1.2542e+01 4.4066e+04 6.8003e+01 3.5135e+05 7.6789e+00 1.0000e+01 6.5800e+02 5.1807e-01 1.4793e+01 5.7635e-01 2.3995e+00 1.8771e-03 1.3502e+01 4.7329e+04 7.1929e+01 3.5053e+05 7.8666e+00

M2(:,:,2)

ans = 12×12

1.0e+00 * 1.0000e+00 1.5880e+03 4.9734e-01 1.5452e+01 1.0599e+00 4.6982e+00 8.4496e-04 5.2795e+00 9.9223e+04 6.2483e+01 1.8794e+06 7.7226e+00 2.0000e+00 1.1260e+03 5.0017e-01 1.4493e+01 7.3674e-01 2.9948e+00 1.7807e-03 9.9620e+00 6.2994e+04 5.5945e+01 6.3234e+05 7.2165e+00 3.0000e+00 6.6100e+02 5.2046e-01 1.5027e+01 6.0794e-01 2.6089e+00 1.3816e-03 8.5906e+00 4.1100e+04 6.2179e+01 4.7843e+05 7.7519e+00 4.0000e+00 6.6200e+02 5.5396e-01 1.3591e+01 6.5171e-01 2.4891e+00 1.4232e-03 8.1271e+00 3.7803e+04 5.7104e+01 4.6515e+05 7.3935e+00 5.0000e+00 6.9600e+02 5.4988e-01 1.4449e+01 4.9721e-01 2.5070e+00 1.5170e-03 1.0182e+01 4.6714e+04 6.7118e+01 4.5879e+05 7.9909e+00 6.0000e+00 6.8100e+02 5.2378e-01 1.5140e+01 6.3404e-01 2.7618e+00 1.4961e-03 1.0019e+01 4.5607e+04 6.6971e+01 4.5520e+05 8.2886e+00 7.0000e+00 7.9000e+02 5.5748e-01 1.3715e+01 5.8097e-01 2.4220e+00 1.7442e-03 1.0771e+01 4.8785e+04 6.1753e+01 4.5293e+05 7.3978e+00 8.0000e+00 7.3400e+02 5.3429e-01 1.3922e+01 5.6176e-01 2.3041e+00 1.6261e-03 9.7424e+00 4.3977e+04 5.9914e+01 4.5140e+05 7.5124e+00 9.0000e+00 8.5800e+02 5.7099e-01 1.2940e+01 5.7602e-01 2.3872e+00 1.9052e-03 1.1222e+01 5.0536e+04 5.8900e+01 4.5035e+05 7.1497e+00 1.0000e+01 9.0300e+02 5.3019e-01 1.3789e+01 5.7253e-01 2.4163e+00 2.0086e-03 1.2033e+01 5.4097e+04 5.9908e+01 4.4957e+05 7.3559e+00

M2(:,:,end)

ans = 12×12

1 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 2 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 3 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 4 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 5 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 6 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 7 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 8 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 9 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 10 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN

That is obviously optional.

.

[Chanille]

@Star Strider This is what I mean:

   for j = 1:nVars
        seg(i) = str2double(ABAP1(i,3));
        seg2(i) = str2double(extractBetween(co(i),2,2));
        la(i) = extractAfter(ABAP1(i,1),2)+"^"+extractBetween(ABAP1(i,1),2,2)+"_"+ABAP1(i,2);
        lb(i) = extractAfter(ABAP1(i,1),2)+"_"+ABAP1(i,2);
        
        C(i,:) = str2double(ABAP1(i,4:nVars + 3));
        
    end

What does this snippet mean? I understand that there's alot of extracting and turning to a string but why is my question specifically for which step and why does the la line give error when i remove a column? Specifically what happens when I have to change the numbers in each line?

[Star Strider]

Please describe in plain language what you want to do, preferably with at least one specific example.

Note that readmatrix does not read the variable names, however readtable does.

[Chanille]

I want to read in the first 7 variables in the provided excel sheet so I can use it for the rest of the code. The first variable will be used to label the points and the next 6 will be used to analyze the variables in analysis. How would I do this with the provided snippet?

[Star Strider]

You can select to read the first seven variables in the readtable call as:

T0 = readtable('exceldata.xlsx', 'Range','A:G')

T0 = 216×7 table
    Slice    Count    Sphericity    AvgFeret    skewness    kurtosis     density  
    _____    _____    __________    ________    ________    ________    __________

      1      1063      0.47472       16.923      1.4261      6.3692      0.0006312
      2      1169      0.49888       15.938      0.7888      3.3704      0.0013679
      3       810      0.51745       14.838     0.62505      2.9444      0.0016288
      4       557       0.5335       15.268      0.3516      2.3852      0.0015122
      5       550      0.54636       14.891     0.50214      2.6001      0.0015251
      6       447      0.54469       14.848     0.42885      2.3657      0.0012531
      7       543      0.53521       14.944     0.70428      2.8828      0.0015328
      8       578      0.53658       14.326     0.49199      2.4976      0.0016393
      9       648      0.53308       14.366     0.53685       2.512      0.0018443
     10       658      0.51807       14.793     0.57635      2.3995      0.0018771
     11       718      0.55385       13.675     0.40135      2.2474      0.0020526
     12       567      0.53844       14.657     0.44447      2.1955      0.0016232
      1      1588      0.49734       15.452      1.0599      4.6982     0.00084496
      2      1126      0.50017       14.493     0.73674      2.9948      0.0017807
      3       661      0.52046       15.027     0.60794      2.6089      0.0013816
      4       662      0.55396       13.591     0.65171      2.4891      0.0014232

To read everything and then select the variables:

T1 = readtable('exceldata.xlsx')

T1 = 216×12 table
    Slice    Count    Sphericity    AvgFeret    skewness    kurtosis     density      normalizedArea    totalArea    avgSize     zoneArea     AvgMinFeret
    _____    _____    __________    ________    ________    ________    __________    ______________    _________    _______    __________    ___________

      1      1063      0.47472       16.923      1.4261      6.3692      0.0006312        4.4013          74122      69.729     1.6841e+06      8.4711   
      2      1169      0.49888       15.938      0.7888      3.3704      0.0013679          8.76          74861      64.038     8.5458e+05       7.909   
      3       810      0.51745       14.838     0.62505      2.9444      0.0016288        10.552          52477      64.786      4.973e+05      7.7483   
      4       557       0.5335       15.268      0.3516      2.3852      0.0015122         10.24          37717      67.715     3.6833e+05      8.2089   
      5       550      0.54636       14.891     0.50214      2.6001      0.0015251        11.005          39687      72.158     3.6062e+05       8.135   
      6       447      0.54469       14.848     0.42885      2.3657      0.0012531        8.7629          31259      69.931     3.5672e+05      8.1118   
      7       543      0.53521       14.944     0.70428      2.8828      0.0015328        10.322          36565      67.339     3.5425e+05       8.083   
      8       578      0.53658       14.326     0.49199      2.4976      0.0016393        10.908          38461      66.542      3.526e+05      7.8097   
      9       648      0.53308       14.366     0.53685       2.512      0.0018443        12.542          44066      68.003     3.5135e+05      7.6789   
     10       658      0.51807       14.793     0.57635      2.3995      0.0018771        13.502          47329      71.929     3.5053e+05      7.8666   
     11       718      0.55385       13.675     0.40135      2.2474      0.0020526        12.903          45135      62.862      3.498e+05      7.1793   
     12       567      0.53844       14.657     0.44447      2.1955      0.0016232        11.361          39686      69.993     3.4932e+05      7.4717   
      1      1588      0.49734       15.452      1.0599      4.6982     0.00084496        5.2795          99223      62.483     1.8794e+06      7.7226   
      2      1126      0.50017       14.493     0.73674      2.9948      0.0017807         9.962          62994      55.945     6.3234e+05      7.2165   
      3       661      0.52046       15.027     0.60794      2.6089      0.0013816        8.5906          41100      62.179     4.7843e+05      7.7519   
      4       662      0.55396       13.591     0.65171      2.4891      0.0014232        8.1271          37803      57.104     4.6515e+05      7.3935   

... it would be much easier to just do:

V1 = T1{:,1}

V1 = 216×1

1 2 3 4 5 6 7 8 9 10

V26 = T1{:,2:6}

V26 = 216×5

1.0e+03 * 1.0630 0.0005 0.0169 0.0014 0.0064 1.1690 0.0005 0.0159 0.0008 0.0034 0.8100 0.0005 0.0148 0.0006 0.0029 0.5570 0.0005 0.0153 0.0004 0.0024 0.5500 0.0005 0.0149 0.0005 0.0026 0.4470 0.0005 0.0148 0.0004 0.0024 0.5430 0.0005 0.0149 0.0007 0.0029 0.5780 0.0005 0.0143 0.0005 0.0025 0.6480 0.0005 0.0144 0.0005 0.0025 0.6580 0.0005 0.0148 0.0006 0.0024

or equivalently:

V26 = T1{:,[2 3 4 5 6]}

V26 = 216×5

1.0e+03 * 1.0630 0.0005 0.0169 0.0014 0.0064 1.1690 0.0005 0.0159 0.0008 0.0034 0.8100 0.0005 0.0148 0.0006 0.0029 0.5570 0.0005 0.0153 0.0004 0.0024 0.5500 0.0005 0.0149 0.0005 0.0026 0.4470 0.0005 0.0148 0.0004 0.0024 0.5430 0.0005 0.0149 0.0007 0.0029 0.5780 0.0005 0.0143 0.0005 0.0025 0.6480 0.0005 0.0144 0.0005 0.0025 0.6580 0.0005 0.0148 0.0006 0.0024

The second option allows you to change the order of the variables in ‘V26’ by changing the order of the column indices inm the ‘T1’ reference.

Of course to do this with the individual reshaped tables (as illustrated in my previous Comment), the addressing would be:

format shortE
M1 = table2array(T1);
M2 = reshape(M1, 12, [], 12);
M2 = permute(M2,[1 3 2]);

M2_17 = M2(:,1:7,:);
M2_17(:,:,1)                                % Show Page #1

ans = 12×7

1.0e+00 * 1.0000e+00 1.0630e+03 4.7472e-01 1.6923e+01 1.4261e+00 6.3692e+00 6.3120e-04 2.0000e+00 1.1690e+03 4.9888e-01 1.5938e+01 7.8880e-01 3.3704e+00 1.3679e-03 3.0000e+00 8.1000e+02 5.1745e-01 1.4838e+01 6.2505e-01 2.9444e+00 1.6288e-03 4.0000e+00 5.5700e+02 5.3350e-01 1.5268e+01 3.5160e-01 2.3852e+00 1.5122e-03 5.0000e+00 5.5000e+02 5.4636e-01 1.4891e+01 5.0214e-01 2.6001e+00 1.5251e-03 6.0000e+00 4.4700e+02 5.4469e-01 1.4848e+01 4.2885e-01 2.3657e+00 1.2531e-03 7.0000e+00 5.4300e+02 5.3521e-01 1.4944e+01 7.0428e-01 2.8828e+00 1.5328e-03 8.0000e+00 5.7800e+02 5.3658e-01 1.4326e+01 4.9199e-01 2.4976e+00 1.6393e-03 9.0000e+00 6.4800e+02 5.3308e-01 1.4366e+01 5.3685e-01 2.5120e+00 1.8443e-03 1.0000e+01 6.5800e+02 5.1807e-01 1.4793e+01 5.7635e-01 2.3995e+00 1.8771e-03

M2_17(:,:,2)                                % Show Page #2

ans = 12×7

1.0e+00 * 1.0000e+00 1.5880e+03 4.9734e-01 1.5452e+01 1.0599e+00 4.6982e+00 8.4496e-04 2.0000e+00 1.1260e+03 5.0017e-01 1.4493e+01 7.3674e-01 2.9948e+00 1.7807e-03 3.0000e+00 6.6100e+02 5.2046e-01 1.5027e+01 6.0794e-01 2.6089e+00 1.3816e-03 4.0000e+00 6.6200e+02 5.5396e-01 1.3591e+01 6.5171e-01 2.4891e+00 1.4232e-03 5.0000e+00 6.9600e+02 5.4988e-01 1.4449e+01 4.9721e-01 2.5070e+00 1.5170e-03 6.0000e+00 6.8100e+02 5.2378e-01 1.5140e+01 6.3404e-01 2.7618e+00 1.4961e-03 7.0000e+00 7.9000e+02 5.5748e-01 1.3715e+01 5.8097e-01 2.4220e+00 1.7442e-03 8.0000e+00 7.3400e+02 5.3429e-01 1.3922e+01 5.6176e-01 2.3041e+00 1.6261e-03 9.0000e+00 8.5800e+02 5.7099e-01 1.2940e+01 5.7602e-01 2.3872e+00 1.9052e-03 1.0000e+01 9.0300e+02 5.3019e-01 1.3789e+01 5.7253e-01 2.4163e+00 2.0086e-03

... and so for the rest.

Indexing into the table or array is much easier than other approaches.

.

[Chanille]

@Star Strider

Thanks I will try this, oh, given the snippet i provided how would i adjust it to accommodate the readtable function as you illustrated?

[Chanille]

@Image Analyst @Star Strider As suggested, here is my full code with readtable but it still is not a working code. Can you please advise:

% Import the entire sheet
ABAP1_full = readtable("HV052923.xlsx", 'Sheet', 'Sheet2');
% Select the range of interest
range = ABAP1_full(2:73, 1:8);
ggmin = 1;
ggmax = 12;
gg = ggmin:ggmax;
per = 5;
sz = size(range);
nObs = sz(1);
nVars = sz(2) - 3;
labels = cell(nObs, 1);
for i = 1:nObs
    labels{i} = range.Slice{i};
end
C = zeros(nObs, nVars);
for i = 1:nObs
    for j = 1:nVars
        C(i, j) = str2double(range{i, j + 2});
    end
end
co = range.Slice + "_" + range.Count;
coo = range.Count;
seg = cellfun(@str2double, range.Count);
seg2 = zeros(nObs, 1);
la = strings(nObs, 1);
lb = strings(nObs, 1);
for i = 1:nObs
    seg2(i) = str2double(extractBetween(co{i}, 1, 1));
    la(i) = extractAfter(range.Slice{i}, 1) + "^" + extractBetween(range.Slice{i}, 1, 1) + "_" + range.Slice{i};
    lb(i) = extractAfter(range.Slice{i}, 1) + "_" + range.Slice{i};
end
C = zscore(C);
[coeff,score,latent,tsquared,explained,mu] = pca(C);
size(coeff)

[Image Analyst]

You forgot to attach "HV052923.xlsx". I'll check back later or tomorrow.