Go through the table with a loop and change values
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I have 30 columns and there are values in these columns. 
2 Comments
Answers (3)
  Subhadeep Koley
    
 on 12 Feb 2020
        
      Edited: Subhadeep Koley
    
 on 12 Feb 2020
  
      ds = record ("xlsfile", "dataset.csv"); 
data = dataset2table(ds); 
[rows, cols] = size(data);
newData = data;
for i = 1: rows
    for j = 1: cols
        if table2array(data(i, j)) == -9
            newData(i, j) = array2table(NaN);
        end
    end
end
7 Comments
  Subhadeep Koley
    
 on 12 Feb 2020
				Your "dataset.csv" is encoded with UTF-16-LE, which is not fully supported by the function readtable. Therefore, I copied and pasted all the data in a new .xlsx file (attached here).
The below code might be helpful now although it is not a very efficient solution.
clc;
data = readtable('Book1.xlsx');
[rows, cols] = size(data);
newData = data;
for i = 1: rows
    for j = 1: cols
        temp = table2array(data(i, j));
        if iscell(temp)
            temp = cell2mat(temp);
        end
        if temp == -9
            newData(i, j) = array2table(NaN);
        end
    end
end
  Steven Lord
    
      
 on 12 Feb 2020
        The standardizeMissing function can accept arrays of various types, including table arrays and timetable arrays. If you only want to standardize the form in which missing data is stored for certain variables in your table you can tell it to only operate on specific 'DataVariables' as well.
0 Comments
  BN
      
 on 12 Feb 2020
        
      Edited: BN
      
 on 12 Feb 2020
  
      I think you won't need to use for loop. If A is the name of the table, then you can just use:
A= readtable('dataset.csv');
A{:,:}(A{:,:}==-9) = NaN
9 Comments
  BN
      
 on 12 Feb 2020
				Oh yes I'm sorry I had a typo, use this:
A= readtable('dataset.csv');
A2 = table2array(A);
A2(A2==-9) = NaN;
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