How to remove all NaN and Inf values when calculate the mean?

I just computed a 167*50 double matrix (Log_ret) mean, with a lot of NaN and +-Inf. I've seen a solution from another question, which is really good. But when I got the extractedData, all the data turn into one column, which means that I got a 6798*1 double variable. So, how can I keep the reult still in their previous column without moving in to one column. (I mean numbers in column 2 after removing all NaN and Inf still in the column2 and column 33 after removing all NaN and Inf still in the column 33 etc.)

Thanks in advance!

mask = (Log_ret ~= 0) & isfinite(Log_ret)
extractedData = Log_ret(mask)

[the cyclist]

To take a smaller example, suppose Log_ret is

Log_ret = [ 2  3 Inf;
           NaN 5  7]

What do want the output extractedData to be? Be specific. There is no such thing as an "empty" slot in a numeric array.

Answer 1

[Matt J]

If you're saying you want to take the column-wise mean, ignoring zeros and non-finite values, then you could do,

exclude =  (Log_ret == 0) | ~isfinite(Log_ret)  ;

extractedData=Log_ret;

extractedData(exclude)=nan;

columnMeans = mean(extractedData,1,'omitnan'); %the result

In other words, you shouldn't approach it by trying to remove NaNs and Infs. You should approach it by converting all values you want to exclude to NaNs and using the omitnan flag, where appropriate.

[Les Beckham]

I'm wondering why you are excluding the zero elements. Doing that will change the mean values. I don't see anything in OP's question about excluding zeros, just +/- Inf and NaN.

[Matt J]

In the OP's code, we see zeros are excluded,

(Log_ret ~= 0)