Average or sum specific-non-sequential columns
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Is there a straight forward quick way to do calculations (sum, mean, etc) on columns that are not in a sequence by avoiding unwanted columns?
For example, if I have 100 rows x10 columns matrix, I would like to do calculations (mean or sum) of all rows in column 1-2, 4, 6-8, and 10. I want to skip column 3,5, and 9.
The matrix of interest looks something like this: Matrix(1:100,1:10), and the columns to be skipped are in an array of their own such as this BadColumns=[3,5,9], I need help of how to avoid the bad columns by implementing the BadColumns array in the code
TheMean=mean(Matrix(:,:),2) %but avoid [3,5,9] in second dimension
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KSSV
le 8 Sep 2021
Let A be your 100x10 matrix. You can remove the said columns from he matrix and use the functions to get what you want.
idx = [3 5 9] ; % index of columns which you dont want to consider
A(:,idx) = [] ; % Remove those columns
Now A has only your required columns. You can get what you want.
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Image Analyst
le 8 Sep 2021
I would have done it somewhat differently than KSSV. You don't need to change your variable - you can keep it the same, just tell mean() what columns to include in the sum:
data = randi(9, 100, 10); % Create sample data
% I have 100 rows x10 columns matrix,
% I would like to do calculations (mean or sum) of all rows in column 1-2, 4, 6-8, and 10.
% I want to skip column 3,5, and 9.
columnsToInclude = [1, 2, 4, 6:8, 10]; % Whatever you want.
theColumnMeans = mean(data(:, columnsToInclude), 1)
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