How to do Table Look-up?

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Logesh Velusamy
Logesh Velusamy on 21 Jan 2020
Commented: dpb on 21 Jan 2020
Hello,
I am trying to reformat a table from 3 columns (Col-1 - Time, Col-2 - VariableName and Col-3 - Value/Data) to more of a map table/Matrix (Time as Rows, VariableNames as Columns) and for any missing data at a times step (for any variable) I want to have "-999" as a default value. I am not sure how do I do this as looping through takes long time to complete populating the matrix which is not a feasible solution.
I have attached images showing 2 tables (imported table with original data and the second is what I want to create from the original table). Please help me in processing this table.
Thanks in advance. :)

Accepted Answer

Guillaume
Guillaume on 21 Jan 2020
Matlab has you covered with unstack:
desired_table = unstack(Processed_Data, 'Value', 'Name')
You'll get NaN for missing values, which is a much better missing indicator than -999. But if you really really want -999 (why?), you can do this afterward:
desired_table = fillmissing(desired_table, 'Constant', -999);
  2 Comments
Logesh Velusamy
Logesh Velusamy on 21 Jan 2020
Hi Guillaume,
Awesome, thanks a lot for your help.
These one line of code is simple and best.
dpb
dpb on 21 Jan 2020
Agreed. Was unaware of unstack.

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More Answers (1)

dpb
dpb on 21 Jan 2020
Edited: dpb on 21 Jan 2020
If all observations are extant but just missing some timesteps, then
vars=unique(data(:,1),'stable'); % unique variable names in data
N=numel(vars); % how many variables there are
t=unique(data(:,2)); % and the time steps found
ttbl=array2timetable(reshape(data(:,3),N,[]).', ...
'RowTimes',seconds(t), ...
'VariableNames',vars);
Then use retime to fill in missing time intervals.
If there are missing observations at a given time, then the above won't work; you'll have to either fix that first or revert to a "find and destroy" method to account for those.
Instead of images, attach data files (smallish examples) for folks to use; nothing can be done with the images other than look.

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