Compute average of a column in a cell without considering NaN values
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I have a cell array with 3 columns and 130000 rows:
A={56276 2009 '-'
56278 2009 NaN
56281 2009 NaN
56285 2009 33.9
56301 2009 '-'
56313 2009 42.5}
I want to have the mean of the values of the third column. If I use the following code,
mean(cell2mat(A(:,3)))
I get an error because I am inlcuding 'NaN' and '-' elements to do the average and I only want to do the average of the numbers.
Can someone help me? Thanks
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Andrew Reibold
2014년 7월 28일
편집: Andrew Reibold
님. 2014년 7월 28일
Do you mean 3 columns and 130,000 rows as is begun in your example?
And I am assuming 42,5 should be 42.5
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Azzi Abdelmalek
2014년 7월 28일
편집: Azzi Abdelmalek
님. 2014년 7월 28일
A={56276 2009 '-'
56278 2009 NaN
56281 2009 NaN
56285 2009 33.9
56313 2009 42.5}
c3=cell2mat(A(2:end,3))
out=nanmean(c3)
%or
out=mean(c3(~isnan(c3)))
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Image Analyst
2014년 7월 28일
It may not be the most compact way, but it's simple and easy to understand:
clc;
A={56276 2009 '-';...
56278 2009 NaN;...
56281 2009 NaN;...
56285 2009 33.9;...
56301 2009 '-';...
56313 2009 42.5}
col3 = A(:,3)
theSum = 0;
counter = 0;
for row = 1 : size(col3, 1)
if isnumeric(col3{row}) & ~isnan(col3{row})
theSum = theSum + col3{row};
counter = counter + 1;
end
end
theMean = theSum / counter
Andrew Reibold
2014년 7월 28일
편집: Andrew Reibold
님. 2014년 7월 28일
Hi Maria,
Here is a rough example of how to get the mean value for EVERY column gathered in your matrix. Its definitely not the best practice, but I think it will work for you.
for clmn = 1:130000
rowsum= 0;
count = 0;
for row = 1:3
if isnumeric(A{rw,clmn}) & ~isnan(A{rw,clmn})
rowsum = rowsum+ A{rw,clmn}
count= count+1
end
end
MeanOfEachColumn(clmn) = rowsum/count;
end
Now if you want the mean of column three, you can just ask for MeanOfEachColumn(3). You can do this with any column you want now.
Variable names are annoyingly long for clarity. I would play with this and let me know if you get errors
I wrote this very quickly and with minimal testing. Let me know if you find walls you can't overcome.
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