Store data into new variable based on condition

I have a n X 10 dataset (variable name = dataset, see attached file). Of interest are column 1 (variable name T) and column 6 (variable name E). What I want to do is this:

1) Compare column 6 values in each cell to a threshold variable (variable name thresh). Identify the cells which are greater than this threshold (i.e. E(:,1) > thresh)

2) For the rows which fulfill condition 1, note the corresponding value in column 1 and find all rows in the dataset which have exactly the same values in column 1 (these are typically a few before or after the row which fulfill condition 1).

3) Copy these rows from condition 2 and store them into new variable data_1.

I have tried this code:

A=max(size(dataset));
T(:,1) = data(:,1);
E(:,1) = data(:,6);
thresh = 85;

for i = 1:A
    if E(i,1)> thresh
        [row, ~]=find(T(:,1)==T(i,1));  
        row_size = max(size(row));
        for j = 1
            data_1(j:j+row_size-1,1:10) = data(min(row):max(row),1:10);
        end
        j=1+row_size;
    end
end

However the answers are wrong. The result in data_1 is a 5x10 variable with incorrect values. Can someone please advice what is going wrong?

Thank you. Regards Ben

[Stephen23]

Splitting data into a variable named data_1 is not a good sign. This might be relevant:

https://www.mathworks.com/matlabcentral/answers/304528-tutorial-why-variables-should-not-be-named-dynamically-eval

Answer 1

[dpb]

Matlab Tutorial (not your problem, but worth noting in general)

A=max(size(dataset)); --> length(dataset)

which will only be number of rows if there are more rows than column. If you want number of rows for sure, then use

nR=size(dataset,1);

For your problem

Step 1:

ix=dataset(:,6)>thresh;  % logical addressing vector of values above threshold

Step 2:

data=dataset(ismember(dataset(:,1),dataset(ix,1)),:);  % match col 1 values in above set to rest of population

[BenL]

thank you, but how does Step 2 actually work?

[dpb]

You've got the subset of the total that satisfy the condition on column 6 as the group selected via the logical indexing array. Then, you wanted to match any of the values in column 1 that were included in that group so ismember returns another logical indexing array of position in the entire dataset, column 1 that are matched by the values in the subset, column 1.

Read

doc ismember % and examples to see "how it works"