Counting occurrences of each column in a matrix
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I have a matrix with 16 columns and a very large number of rows. Each column has two possible outcomes in it (for example 1 or 0 in one column, .6 and .4 in another). I would like to count each of these occurrences in the columns. Preferably, I'd like to have a vector that counts each outcome of its respective column. Thank you!
[EDITED, Jan, moved from section for answers]
Example: A = [1 .6 .7 .8; 0 .4 .3 .2; 1 .6 .7 .8; 1 .6 .3 .8]
ans = [3 3 2 2 ; 1 1 2 2]
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Jan
2018-10-8
The example is not clear: 0.8 occurs 3 times, so shouldn't the last value of the output be 3 or perhaps 1? Why is the first column of the output [3;1] and not [1;3]?
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ANKUR KUMAR
2018-10-8
Since you have not given any sample data, I am taking some random data.
A=randi(50,50,50);
A(A<=25)=0.4;
A(A>25)=0.6;
A contains only 0.4 and 0.6 only, spreaded out completely. The below program gives you the occurrence of 0.4 and 0.6 in every coloumn.
nums1=arrayfun(@(x) length(find(A(:,x)==0.4)),1:size(A,2));
nums2=arrayfun(@(x) length(find(A(:,x)==0.6)),1:size(A,2));
occur=[nums1' nums2'];
nums2 can also be calculated as
nums2=size(A,1)-nums1;
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dpb
2018-10-8
Several ways to do this; probably easiest is via converting to categorical with the unique values in each column transformed to a single pair of categories--[0|1], [Y|N], [HI|LO], ..., whatever makes sense for the meanings.
Then histogram on those variables to return counts.
Or, use unique and the returned (optional) second index array to bin over.
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