PCA.m with data containing NaN (ncnancov.m bug ?)

I can run the following,

    data = randn(2.7E6,79);
    [~,score,~,~,explained, ~] = pca(data);

I also have a real data matrix of the same size (79 variables, 2.7E6 observations).

Each row ( i.e. time step) has at least one NaN, in one of the variables. Because of this localSVD.m returns a blank. ie pca.m fails.

I can not replace the NaN with zero as this will change the data (the data is a differenced time series, hence zero means something very different to NaN).

I then try a different approach,

[~,score,~,~,explained, ~] = pca(data,'Algorithm','eig', 'Rows', 'pairwise');

the code fails,

Error using eig
Input to EIG must not contain NaN or Inf.

Error in pca>localEIG (line 441)
[coeff, eigValueDiag] = eig(xCov);

Error in pca (line 308)
    [coeff, eigValues] = localEIG(x, vCentered, vRows, vWeights,...

Error in cce_moonShine_L1_PCA (line 28)
[~,score,~,~,explained, ~] = pca(data,'Algorithm','eig', 'Rows', 'pairwise');

I then inspect the cov matrix (79*79)

imagesc(isnan(xCov))

and see that one row/col is NaN. It seems like ncnancov.m is failing as it is outputting with NaN in it?

I also get this when trying,

xCov = nancov(x,'pairwise');

suggestions? How can I carry out PCA on this data?

[Stephen23]

Eric's "Answer" moved here:

Hello? This just happened to me too. Does anyone from MATHWORKS want to reply?