reshaping tables and calculating combination of differences between variables

 Hi all,
I would like to reshape the following table 
  Area    time    rates
   A1  2008       13 
   A1  2009  12
   A2  2008  11
   A2  2009  9
   A3  2008  7
   A3  2009  13
   A4  2008  6
   A4  2009  7
   A5  2008  9
   A5  2009  5

to this one

Time A1 Aa2 A3 A4 A5

2008 13 11 7 6 9

2009 12 9 13 7 8

and then extend the table with the following colums

time DA12 DA13 DA14 DA15 DA23 DA24 DA25 DA34 DA35 DA45

2008

2009

Where DA12=difference between area 1 and area 2. Similarly for the rest. Is it possible to write a code that will calculate all the combinations of the differences between these areas "quickly"because i have 50 such areas across a long period of time.

thanks in advance

[Jan]

The question is not clear. What does "table" mean? An Excel table, UITABLE, a cell or a formatted text file? What is the "area 1" required for "DA12"? What are the "combinations" and ehat means "quickly" - in microseconds? What is a "long period of time"?

[ektor]

Thank you Simon.

The table is in an excel table and i want to convert it to the following form

Time A1 Aa2 A3 A4 A5

2008 13 11 7 6 9

2009 12 9 13 7 8

using matlab code, this is my first question. then i want to create additional colums, for example the column DA12 which is defined as follows

time DA12

2008 13-11 (the valu of A1 for the year 2008-the value of A2 for the year 8)

2009 12-9

So as you can see i want to calculate the difference of interest rates between areas for teach period ( 2008 and 2009.) and because I have many areas( in our example 5 areas) there are many combinations of such pair of areas. So, when i say "quickly'" i mean to be able to calculate all thesee pairs using matlab code. I hope to be more explicit this time

thank you again

Unless there is a completely different approach in obtaining these differences

[Ory]

I have the same question, as far as the 1st part is concerned: how do you pivot data in Matlab without using for loops? In R one can do it using the Reshape package for example, where one can 'melt' the dataset and 'cast' it into a new shape.