Join Matrices in MATLAB - matlab

Question

I have two matrices like the following ones:
'01/01/2010' 1
'02/01/2010' 2
'03/01/2010' 3
'05/01/2010' 11
'06/01/2010' 17
'01/01/2010' 4
'02/01/2010' 5
'04/01/2010' 6
'05/01/2010' 7
, and after doing a few tricky things in MATLAB, I want to create the following three matrices:
'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
'01/01/2010' 1 4
'02/01/2010' 2 5
'05/01/2010' 11 7
Any idea on how to join these tables?
Cheers.
EDIT: Really sorry for my typos, guys. I updated both the question and the input/output data. Please, feel free to provide suggestions.

Answer 1

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]

Answer 2

In MATLAB, you cannot have strings as matrix elements. For that you need to use a cell array. This is a solution using cell arrays and containers.Maps.
FirstCellArray = {
'01/01/2010', 1;
'02/01/2010', 2;
'03/01/2010', 3;
'05/01/2010', 11;
'06/01/2010', 17
};
SecondCellArray = {
'01/01/2010', 4;
'02/01/2010', 5;
'04/01/2010', 6;
'05/01/2010', 7;
};
AllDatesCellArray = union(FirstCellArray(:,1), SecondCellArray(:,1));
% Create containers.Maps for both cell arrays. containers.Maps are hash tables.
DateToFirstNumberMap = containers.Map(FirstCellArray(:,1), FirstCellArray(:,2));
DateToSecondNumberMap = containers.Map(SecondCellArray(:,1), SecondCellArray(:,2));
WithNaNsCellArray = AllDatesCellArray;
for Index = 1:size(WithNaNsCellArray, 1)
Key = AllDatesCellArray{Index, 1};
try
NumberOne = cell2mat(values(DateToFirstNumberMap, cellstr(Key)));
catch
NumberOne = NaN;
end
WithNaNsCellArray{Index, 2} = NumberOne;
try
NumberTwo = cell2mat(values(DateToSecondNumberMap, cellstr(Key)));
catch
NumberTwo = NaN;
end
WithNaNsCellArray{Index, 3} = NumberTwo;
end
WithoutNaNsCellArray = WithNaNsCellArray;
NaNIndicesVector = (isnan([WithNaNsCellArray{:,2}]) | isnan([WithNaNsCellArray{:,3}]));
WithoutNaNsCellArray(NaNIndicesVector == 1, :) = [];
Then WithNaNsCellArray contains the result with NaN rows and WithoutNaNsCellArray contains the result without NaN rows.
WithNaNsCellArray =
'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]
WithoutNaNsCellArray =
'01/01/2010' [ 1] [4]
'02/01/2010' [ 2] [5]
'05/01/2010' [11] [7]

Answer 3

The statistics toolbox contains a function called JOIN that basically does what you want.
http://www.mathworks.de/de/help/stats/dataset.join.html
Unfortunately, it probably can't handle strings and polytyped matrices. But you might be able to use JOIN to shorten the solutions proposed by the other answers.