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How do I count the number of NaNs in a Vector?

Jason Baxter さんによって質問されました 2012 年 8 月 7 日
I have an nxm array a(n,m) with an unknown number of NaNs inside. I want to look for the column a(i,:) which contains the least number of Nans, how do I do this?
thank you for your help

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3 件の回答

Daniel Shub
回答者: Daniel Shub
2012 年 8 月 7 日
 採用された回答

This is a straight forward question and given you haven't shown any attempt to solve it, I am hesitant to provide an answer ...
Start by making some nonsense data
n = 10;
m = 5;
a = randn(n, m);
a(rand(numel(a), 1) < 0.25) = nan;
a =
0.5377 -1.3499 0.6715 0.8884 NaN
1.8339 3.0349 -1.2075 -1.1471 NaN
-2.2588 0.7254 0.7172 -1.0689 0.3192
NaN -0.0631 NaN -0.8095 0.3129
NaN 0.7147 0.4889 -2.9443 -0.8649
-1.3077 -0.2050 1.0347 1.4384 NaN
-0.4336 -0.1241 NaN 0.3252 -0.1649
0.3426 NaN -0.3034 -0.7549 0.6277
3.5784 NaN 0.2939 1.3703 NaN
NaN 1.4172 -0.7873 -1.7115 1.1093
The ISNAN function tells you if an element is a nan (1) or not (0).
isnan(a)
ans =
0 0 0 0 1
0 0 0 0 1
0 0 0 0 0
1 0 1 0 0
1 0 0 0 0
0 0 0 0 1
0 0 1 0 0
0 1 0 0 0
0 1 0 0 1
1 0 0 0 0
Now we want to sum up all the ones in each column. We have the SUM function that does that
sum(isnan(a))
ans =
3 2 2 0 4
To get the final answer we want to find which column has the smallest sum. The MIN function usually returns the smallest values, but if you read the documentation, the second output argument is the index of the minimum value.
[~, col] = min(sum(isnan(a)))
col =
4
where the ~ notation allows for the first output argument to be ignored.

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Jason Baxter 2012 年 8 月 7 日
sorry, I haven't attempted it because I had no idea how to answer it, i'm not very good at Matlab yet. Thank you Daniel for your answer, I will answer more questions than I ask to keep the community going when I have time. Thank you for your answer! Jason

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Oleg Komarov
回答者: Oleg Komarov
2012 年 8 月 7 日

[minval,idx] = min(sum(isnan(a)))

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Azzi Abdelmalek
回答者: Azzi Abdelmalek
2012 年 8 月 7 日
編集済み: Azzi Abdelmalek
2012 年 8 月 7 日

s=sum(isnan(a)); %
[dd,ff]=min(s);
find(s==dd) % gives the rows that contain the least "nan"
% it's possible there are many rows containing the least nan

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