Join Matrices in MATLAB

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迷失自我
迷失自我 2020-12-06 08:51

I have two matrices like the following ones:

\'01/01/2010\'          1
\'02/01/2010\'          2
\'03/01/2010\'          3
\'05/01/2010\'         11
\'06/01/         


        
3条回答
  •  我在风中等你
    2020-12-06 09:20

    I believe what you are trying to achieve are called inner join, and full outer join in the database world.

    First we start with the two datasets:

    d1 = {
     '01/01/2010'          1
     '02/01/2010'          2
     '03/01/2010'          3
     '05/01/2010'         11
     '06/01/2010'         17
    };
    d2 = {
     '01/01/2010'          4
     '02/01/2010'          5
     '04/01/2010'          6
     '05/01/2010'          7
    };
    

    Here is the code to perform the two types of join:

    %# get all possible dates, and convert them to indices starting at 1
    [keys,~,ind] = unique( [d1(:,1);d2(:,1)] );
    
    %# full outer join
    ind1 = ind(1:size(d1,1));
    ind2 = ind(size(d1,1)+1:end);
    
    fullOuterJoin = cell(numel(keys),3);
    fullOuterJoin(:) = {NaN};           %# fill with NaNs
    fullOuterJoin(:,1) = keys;          %# union of dates
    fullOuterJoin(ind1,2) = d1(:,2);    %# insert 1st dataset values
    fullOuterJoin(ind2,3) = d2(:,2);    %# insert 2nd dataset values
    
    %# inner join
    loc1 = ismember(ind1, ind2);
    loc2 = ismember(ind2, ind1);
    
    innerJoin = cell(sum(loc1),3);
    innerJoin(:,1) = d1(loc1,1);        %# intersection of dates
    innerJoin(:,2) = d1(loc1,2);        %# insert 1st dataset values
    innerJoin(:,3) = d2(loc2,2);        %# insert 2nd dataset values
    

    Alternatively, we could have extracted the inner join from the outer join dataset by simply removing rows with any NaN values:

    idx = all(~isnan(cell2mat(fullOuterJoin(:,2:end))), 2);
    innerJoin = fullOuterJoin(idx,:);
    

    Either way, the result:

    >> fullOuterJoin
    fullOuterJoin = 
        '01/01/2010'    [  1]    [  4]
        '02/01/2010'    [  2]    [  5]
        '03/01/2010'    [  3]    [NaN]
        '04/01/2010'    [NaN]    [  6]
        '05/01/2010'    [ 11]    [  7]
        '06/01/2010'    [ 17]    [NaN]
    
    >> innerJoin
    innerJoin = 
        '01/01/2010'    [ 1]    [4]
        '02/01/2010'    [ 2]    [5]
        '05/01/2010'    [11]    [7]
    

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