A for loop extracting every new variable into column vectors?

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Hi! I have the following stacked table, and I need to be able to extract/refer to every new element that appears at ChElem_Indicator (column 8) with the correspondent value that appears at ChElem (column 9). The ChElem_Indicator contains repeated data, with the elements (for example "Si") appearing hundreds of times.
Every time a new ChElem_Indicator variable appears, I'd like to create a column vector (with the name of that variable) that extracts the corresponding value from ChElem column. Scanning the entire table, my goal is to end up with, for example, a column vector "Si" with all values which are related to "Si", and to have this for all the different variables that appear in ChElem_Indicator column (not only "Si"). I think a for loop is what I need, but I don't know how to incorporate the part "for every new variable".
Any ideas/suggestions? Thanks in advance!
  2 个评论
Stephen23
Stephen23 2018-2-6
编辑:Stephen23 2018-2-6
'I think a for loop is what I need, but I don't know how to incorporate the part "for every new variable".'
Do NOT do this! Magically accessing variable names in a loop is how beginners force themselves into writing slow, complex, buggy code:
'my goal is to end up with, for example, a column vector "Si" with all values which are related to "Si", and to have this for all the different variables that appear in ChElem_Indicator column (not only "Si").'
'Any ideas/suggestions?'
Use one of the table class methods to group the rows based on that column, such as
or
Ana Castanheiro
Ana Castanheiro 2018-2-7
Thanks for sharing your advices and suggestions, these are especially important for a Matlab beginner as myself.

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回答(1 个)

Guillaume
Guillaume 2018-2-6
[groupid, groupname] = findgroups(ClustSEMdata.ChElem_Indicator);
elements = splitapply(@(v) {v}, ClustSEMdata.ChElem, groupid);
result = cell2table(elements.', 'VariableNames', groupname)
It sounds like you want to create individual variables for each element, which would be a very bad idea. Putting them in a table as above, a cell array, a map, or a structure would be a lot better.
  1 个评论
Ana Castanheiro
Ana Castanheiro 2018-2-7
Many thanks for your reply Guillaume. This piece of code works nicely but only partially for what I was asking about. Based on your and Stephen's comments, I now understand that creating individual variables for each element is not a good idea. I had created the table in the image using the stack function, but probably this is not necessary at all, and I should instead work with the original table (where every column is already a different chemical element).
What I need is to be able to do some clustering analysis, for which I need to start with the code below. So, perhaps the best is that I use:
treedata = [ originaldata.Al, originaldata.Si, originaldata.Fe];
%%desired treedata = [Al, Si, Fe];
dist = pdist(treedata,'euclidean');
linkmethod = 'ward';
tree = linkage(dist,linkmethod);
figure()
dendrogram(tree, 0, 'orientation', 'right')
title(sprintf('%s%s %d', det1{1:2},det1{3}))

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