Replacing Negative Values in Table with Previous Value in Column

I have a table 17520x5, in the last 2 columns I would like to replace all negative values with the previous value in that column. This is what I have tried so far and it is not working I still get negative values shown.

My table (T) had 5 columns, variable labels are (A, B, C, D, E) for each column for example

D(D < 0) = NaN;
E(E < 0) = NaN;
T(:, {'D', 'E'}) = fillmissing(T(:,{'D', 'E'}), 'previous');
disp(T)

Answer 1

[Matt J]

T(:, {'D', 'E'}) = num2cell( fillmissing([D,E], 'previous')  );

[Stef1998]

thank you but this now shows an error that the number of rows does not match the height of the table

[Matt J]

We can try an example to show that it works:

T=array2table( rand(4,5)-0.5 ,'Var',{'A','B','C','D','E'});
D=T{:,4}; E=T{:,5};
D(D < 0) = NaN;
E(E < 0) = NaN;

T,

T = 4×5 table
       A          B           C           D           E    
    _______    ________    ________    ________    ________

    0.44208     0.49326     0.12868     0.42218     0.43518
    0.24954    -0.42086    -0.39169    -0.31886    -0.13442
    0.38232     -0.3545    -0.49562    -0.47566    -0.15402
    0.28615      0.3741     0.11841    -0.16468     0.48483

T(:, {'D', 'E'}) = num2cell( fillmissing([D,E], 'previous')  )

T = 4×5 table
       A          B           C           D          E   
    _______    ________    ________    _______    _______

    0.44208     0.49326     0.12868    0.42218    0.43518
    0.24954    -0.42086    -0.39169    0.42218    0.43518
    0.38232     -0.3545    -0.49562    0.42218    0.43518
    0.28615      0.3741     0.11841    0.42218    0.48483

[Stef1998]

Thank you so much! It worked

Answer 2

[Peter Perkins]

Stef, as near as I can tell, the only thing wrong with your original solution is that D and E are in T, not in the workspace. The following works fine, including repeated negative values and negative values in the first row. There's no need to explicitly pull D and E out of the table. Using Matt's setup:

>> T = array2table(rand(4,5)-0.5 ,'Var',["A" "B" "C" "D" "E"])
T =
  4×5 table
       A           B            C           D            E    
    ________    ________    _________    ________    _________
    -0.33782    -0.33435      0.18921    -0.27102     0.038342
     0.29428     0.10198      0.24815     0.41334      0.49613
    -0.18878    -0.23703    -0.049458    -0.34762     -0.42182
    0.028533     0.15408     -0.41618     0.32582    -0.057322
>> T.D(T.D < 0) = NaN;
>> T.E(T.E < 0) = NaN
T =
  4×5 table
       A           B            C           D          E    
    ________    ________    _________    _______    ________
    -0.33782    -0.33435      0.18921        NaN    0.038342
     0.29428     0.10198      0.24815    0.41334     0.49613
    -0.18878    -0.23703    -0.049458        NaN         NaN
    0.028533     0.15408     -0.41618    0.32582         NaN
>> T(:, ["D" "E"]) = fillmissing(T(:,["D" "E"]), 'previous')
T =
  4×5 table
       A           B            C           D          E    
    ________    ________    _________    _______    ________
    -0.33782    -0.33435      0.18921        NaN    0.038342
     0.29428     0.10198      0.24815    0.41334     0.49613
    -0.18878    -0.23703    -0.049458    0.41334     0.49613
    0.028533     0.15408     -0.41618    0.32582     0.49613