standardizeMissing not working on all table columns

I have a table which contains some columns of numbers, some columns of cells which contain multiple numbers, and some columns of strings.

I've attached a .mat file with a section of this table.

I've set certain values to 999, which I later want to change to NaN using the function 'standardizeMissing'. However, this function appears to work for all columsn except for one (column 15, called 'sheepCOM_transport').

This column appears to be a cell containing either 999 or an array of two values.

How can I replace the values of 999 with NaN in this column? Can standardizeMissing work with this column?

I've tried:

T = standardizeMissing(T.sheepCOM_transport, {999});

and

 Tc = T.sheepCOM_transport;
 Tc = cell2table(Tc);
 Tc = standardizeMissing(Tc, 999);
 T.sheepCOM_transport = Tc;

But these solutions dont seem to work.

Answer 1

[Peter Perkins]

standardizeMissing isn't designed to dig into arbitrary cell arrays. If "valid" values in that cell array are always two-element row vectors, then I'm gonna suggest that you turn those cell arrays into two-column matrices. I think in the long run you'll be happier.

>> c = {1:2; 999; 3:4; 999}
c =
  4×1 cell array
    {1×2 double}
    {[     999]}
    {1×2 double}
    {[     999]}
>> missing = cellfun(@(x) isequal(x,999),c)
missing =
  4×1 logical array
   0
   1
   0
   1
>> c(missing) = {[NaN NaN]}
c =
  4×1 cell array
    {1×2 double}
    {1×2 double}
    {1×2 double}
    {1×2 double}
>> c = vertcat(c{:})
c =
     1     2
   NaN   NaN
     3     4
   NaN   NaN

OTOH, if the entries can be vectors of different sizes, then you are right to stick with a cell array.

[Centauri Jolene]

This is a better answer, since it results in a data format that is easier to work with in the long run. Thank you Peter.

Answer 2

[KSSV]

L = cellfun(@length,T.sheepCOM_transport) ; 
T.sheepCOM_transport(L==1) = {NaN} ; 

[Centauri Jolene]

Thanks!