creating a string multiple string filter on multiple columns
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Hello, I have a n x m (row-column data) that I previously was able to do some basic analysis on.
How can I create a multiple "string filter" for each column and remove the unwanted "strings" , after filtering I then need to concatenate the column after removing the unwanted strings.
data = randn(n,m);
results = cell(1,m);
for jj = 1:m
results{jj} = perform_analysis(data(:,jj));
end
Example:
First Filter is AA, BB, CC, DD (independent of each other) then concatenate "some data" on the column x.
Continue this type of filter until all columns have removed the unwanted strings while the data is concatenated for all columns.
Thanks...
3 个评论
DGM
2022-2-7
Can you provide an example of an input array, the strings to be removed, and the intended resultant output?
Michael Angeles
2022-2-7
HI DGM,
the Example array would be something like below but stores the whole new filtered data into a new n x m array variable. I was thinking of a nested for loop but I couldn't get it to work...
Jan
2022-2-7
I do not understand, what you are asking for. What does this mean: concatenate "some data" on the column x ?
What is the shown table? A string array? Then setdiff should work.
采纳的回答
dpb
2022-2-7
Without knowing the real application and how the data are obtained so it is presumed to already be character type,
>> n=16;m=2;data =cellstr(char(randi([65 70],n,m)))
data =
16×1 cell array
{'FC'}
{'FE'}
{'DD'}
{'AD'}
{'AF'}
{'BB'}
{'FE'}
{'BE'}
{'EC'}
{'BD'}
{'FA'}
{'CA'}
{'BD'}
{'BE'}
{'DF'}
{'CA'}
>> result=data(~matches(data,{'AA','BB','CC','DD'}))
result =
14×1 cell array
{'FC'}
{'FE'}
{'AD'}
{'AF'}
{'FE'}
{'BE'}
{'EC'}
{'BD'}
{'FA'}
{'CA'}
{'BD'}
{'BE'}
{'DF'}
{'CA'}
>>
Since you pasted an image instead of data, the starting array is the same; pasting in the actual example data is much better for responders and more likely to get solution to particular problem if it is more highly data-dependent than this particular one.
If OTOH, the data are really generated as numeric and then combined as above, then one can get their directly from the numerics...
>> result=cellstr(char(data(data(:,1)~=data(:,2),:)))
result =
14×1 cell array
{'FC'}
{'FE'}
{'AD'}
{'AF'}
{'FE'}
{'BE'}
{'EC'}
{'BD'}
{'FA'}
{'CA'}
{'BD'}
{'BE'}
{'DF'}
{'CA'}
>>
3 个评论
dpb
2022-2-8
Alternative to the ~match route is
result=setdiff(data,{'AA','BB','CC','DD'});
Michael Angeles
2022-2-9
How would you reshape this array into 2D after removing the matches?
A = {'AA' 'AB' 'AC'; 'BB' 'BA' 'BC'; 'CA' 'CB' 'CC'}
Arrays must be rectangular, so what is an acceptable workaround? Padding the columns with empty cells?
更多回答（1 个）
Assuming you're dealing with a cell array of chars or string arrays:
A = {'AA'; 'AB'; 'BA'; 'BB'; 'AC'; 'CA'; 'BC'; 'CB'; 'CC'};
toremove = {'AA','BB','CC'};
% you could do it with ismember()
B = A(~ismember(A,toremove))
% or you could use setdiff()
C = setdiff(A,toremove,'stable')
2 个评论
Michael Angeles
2022-2-9
It should work fine on 2D arrays, but you have to realize that the result will necessarily not be 2D anymore.
A = {'AA'; 'AB'; 'BA'; 'BB'; 'AC'; 'CA'; 'BC'; 'CB'; 'CC'};
A = [A A(randperm(numel(A))) A(randperm(numel(A)))]; %replicate to 3 columns
toremove = {'AA','BB','CC'};
% you could do it with ismember()
B = A(~ismember(A,toremove))
% or you could use setdiff()
C = setdiff(A,toremove,'stable')
Note that setdiff() returns only the unique values, whereas using ismember() returns everything. Since A in this case is three randomly permuted copies of the same column, the result from B is three times that of C, as it contains three copies of each matching element.
If you are getting errors, you'll have to describe exactly what you're doing and what error you're getting.
EDIT:
Regarding columnwise filtering and padding:
A = {'AA'; 'AB'; 'BA'; 'BB'; 'AC'; 'CA'; 'BC'; 'CB'; 'CC'};
A = repmat(A,[1 3]);
A(:) = A(randperm(numel(A))) % 3x3 but matches aren't uniformly distributed
toremove = {'AA','BB','CC'};
B = cell(size(A));
maxr = 0;
for c = 1:size(A,2)
thisb = A(~ismember(A(:,c),toremove),c);
B(1:numel(thisb),c) = thisb;
maxr = max(maxr,numel(thisb));
end
B = B(1:maxr,:)
Alternatively, you could put each column in a nested cell array:
B = cell([1 size(A,2)]);
maxr = 0;
for c = 1:size(A,2)
B{c} = A(~ismember(A(:,c),toremove),c);
end
B
Again, similar can be done with setdiff() if you only want the unique results.
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