How to turn NaN values in only numerical columns into -999?
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I have some data with both numerical and string columns. See attached for an example (aa.xlsx).
It has four columns like this:
Header1 Header2 Header3 Header4
1, 4, -9, ABC123
2, NaN, 0, NaN
5, 6, NaN, ABC789
My goal is to convert any NaN values that are in only numerical columns into -999, while leaving the NaN values in string columns intact. The end results should look like something like this:
Header1 Header2 Header3 Header4
1, 4, -9, ABC123
2, -999, 0, NaN
5, 6, -999, ABC789
Here is the code I know will work, if all of my columns are numerical:
%convert any NaN into -999
T1 = readtable ('aa.xlsx', 'PreserveVariableNames',true)
Ind_table = isnan(T1{:,:});
T1{:,:}(Ind_table) = -999;
How should I modify it so that it won't do the conversion for columns that are made up of strings?
Many thanks!
Accepted Answer
More Answers (2)
Sebastian Bomberg
on 17 Oct 2019
You can have fillmissing apply only to the numeric variables directly:
fillmissing(T1,"constant",-999,"DataVariables",@isnumeric)
Walter Roberson
on 17 Oct 2019
fillmissing(T1,'constant',{-999,-999,-999,'NaN'})
Note that this will use the character vector 'NaN' (three characters) in place of the numeric NaN entries in column 4, as it is not possible to have numeric entries in a column devoted to character vectors.
5 Comments
Walter Roberson
on 17 Oct 2019
char_vars = varfun(@iscell, T1, 'OutputFormat', 'uniform');
constants = num2cell(-999*ones(1,width(T1)));
constants(char_vars) = {'NaN'};
new_T1 = fillmissing(T1, 'constant', constants);
Leon
on 17 Oct 2019
Adam Danz
on 17 Oct 2019
You can always unaccept / accept; I don't mind :)
Leon
on 17 Oct 2019
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