Horizontally join two datasets of different sizes based on a common field

Dear all,

I have two matrices (A and B) that I want to join together horizontally based on a common field to create an output as shown in C. I have included a small example of my very large datasets:

A=

        3304  1  329  0
        3304  1  819  0
        3304  2  76  0
        3304  1  12  0
        3304  2  971  1
        3304  1  76  2
        3304  2  230  2
        3304  1  258  2
        3304  1  27  3
        3304  1  73  3
        3304  2  179  3
        3304  3  190  3

B=

0  29.7  27.7  13.2
1  26.3  24.3  14.1
2  28.1  26.1  24.5
3  27.1  25.1  13.1

C=

3304  1  329  0  0  29.7  27.7  13.2
3304  1  819  0  0  29.7  27.7  13.2
3304  2  76  0  0  29.7  27.7  13.2
3304  1  12  0  0  29.7  27.7  13.2
3304  2  971  1  1  26.3  24.3  14.1
3304  1  76  2  2  28.1  26.1  24.5
3304  2  230  2  2  28.1  26.1  24.5
3304  1  258  2  2  28.1  26.1  24.5
3304  1  27  3  3  27.1  25.1  13.1
3304  1  73  3  3  27.1  25.1  13.1
3304  2  179  3  3  27.1  25.1  13.1
3304  3  190  3  3  27.1  25.1  13.1

I have spent many hours on this what I imagine is a very simple task, so any help would be appreciated.

Answer 1

[Thorsten]

C = [A B(A(:,4)+1, :)];

[Lucy]

Many thanks!

[Guillaume]

This answer assumes that the first column of B is always 0,1,2,3,4,etc. in that order, with no gap. A more generic solution, which works regardless of the ordering and values of B's first column:

[tf, ib] = ismember(A(:, 4), B(:, 1));
C = [A(tf, :) B(ib, :)];

The above also works if the common field is not found in B (it just does not include that row).

[Lucy]

Great, this will be very useful. Much appreciated