Ignore NaN and -9999 values

T_new = standardizeMissing(T, 0);
T_new = standardizeMissing(T_new, -9999)
A = T_new(:,vartype('numeric'));
omean = @(x) mean(x,'omitnan'); %ignoring NaN
mean_values = varfun(omean,A)

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Steven Lord 2020-4-10

在 MATLAB Online 中打开

You don't need to call standardizeMissing twice. It accepts a vector of values that should be converted to the standard missing value (which is NaN for double precision arrays.) Using a slightly modified version of the first example from its documentation page:

A = [0 1 5 -99 8 3 4 -99 16];
B = standardizeMissing(A,[-99, 0]);
beforeAndAfter = [A; B]

The 0 and the two -99 values in A were replaced by NaN in B.

BN 2020-4-10

Thank you for let me know.

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Answer 2

Ameer Hamza 2020-4-10

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此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/516972-ignore-nan-and-9999-values#answer_425264

编辑：Ameer Hamza 2020-4-10

在 MATLAB Online 中打开

% generting an example table
t = [1 2 3 4 5;
     0 2 1 3 -9999;
     -9999 5 7 0 9;
     nan 1 2 3 -9999];
T = array2table(t);
values = T.Variables;
mask = isnan(values) | values==0 | values==-9999;
values(mask) = nan;
result = nanmean(values, 1)