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RE: st: Reshaping


From   "Nick Cox" <n.j.cox@durham.ac.uk>
To   <statalist@hsphsun2.harvard.edu>
Subject   RE: st: Reshaping
Date   Tue, 11 Nov 2008 18:15:57 -0000

In addition to Neil's excellent advice, I have a few marginal comments. 

Neil kindly gave a plug for -renvars-. However, he guessed wrong about where it should be installed from. -findit renvars- shows that the latest version was published in the Stata Journal. 

Pavlos' data structure reminds me of a similar example in 

SJ-7-2  dm0031  . . . . . . . . .  Stata tip 45: Getting those data into shape
        . . . . . . . . . . . . . . . . . . . . . . . C. F. Baum and N. J. Cox
        Q2/07   SJ 7(2):268--271                                 (no commands)
        tip on applications of reshape and solving data
        management problems

Finally, I disagree about -xpose-. -xpose- will not cope gracefully with string identifiers. In fact, only rarely is -xpose- the answer to anybody's problem. -reshape- is indeed the place to look. 

Nick 
n.j.cox@durham.ac.uk 

Neil Shephard

I could be obtuse and simply say read -man reshape- and you would do
well to do so as without understanding how the command works you will
continue to rely on others to help you with the solution.

The following should do what you want though...

reshape long year_, i(Country measure) j(year)
reshape wide year_, i(Country year) j(measure) string
/* Optionally rename using -renvars- from ssc, if not installed -ssc
inst renvars- */
renvars year_*, presub("year_" "")

You can probably achieve the same results using -xpose- but its slightly
more tricky as you would have to loop over each country appending the
resulting datasets into one large one.

Pavlos C. Symeou wrote:

> I have panel data in the following format (actually yearly data extend
> up to year_2007):
>
> Country     measure     year_1990     year_1991     year_1992    
> year_1993 year_1994     year_1995
> Argentina     gdp_constant     182,63     201,81     222,59    
> 236,51     250,31     243,19
> Argentina     gdp_deflator     37,74     89,64     101,82     100    
> 102,85     106,11
> Argentina     gdp_percap_const     5614,3     6120,91     6660,41    
> 6972,96 7286,34     6992,31
> Argentina     gdp_percap_current     4344,82     5750,51    
> 6845,48     6972,96   7493,95     7419,16
> Argentina     gdp_ppp     182,37     208,56     235,33     255,81    
> 276,5     274,13
> Argentina     gdp_ppp_percap     5606,06     6325,71     7041,58    
> 7542,26 8048,73 7881,97
> Argentina     ppp_conversion_rate     0,38     0,87     0,96    
> 0,93     0,93     0,94
> Argentina     cpi     23,21     63,05     78,75     93,33    
> 97,23     100,52
> Argentina     population     32,53     32,97     33,42     33,92    
> 34,35     34,78
> Australia     gdp_constant     581,27     574,22     586,19    
> 608,95     640,25     663,04
> Australia     gdp_deflator     70     71,54     72,71     73,6    
> 74,16     75,49
> Australia     gdp_percap_const     34011,52     33167,52    
> 33462,01     34411,12 35799,96 36624,29
> Australia     gdp_percap_current     18601,81     18486,94    
> 17889,14 17225,66 19424,37 20499,27
> Australia     gdp_ppp     299,35     306,06     319,63     339,71    
> 364,76     385,47
> Australia     gdp_ppp_percap     17515,56     17678,38    
> 18245,57     19196,38 20395,62     21292,13
> Australia     ppp_conversion_rate     1,36     1,34     1,33    
> 1,32     1,3     1,3
> Australia     cpi     80,35     82,94     83,76     85,28     86,9    
> 90,93
> Australia     population     17,09     17,31     17,52     17,7    
> 17,88     18,1
>

> I need to reshape them in the following format:
>
> Country        year   gdp_constant   gdp_deflator gdp_percap_const  
> gdp_percap_current   gdp_ppp  gdp_ppp_percap ppp_conversion_rate cpi  
> population
> Argentina   1990
> Argentina   1991
> Argentina   1992
> Argentina   1993
> Argentina   1994
> Argentina   1995
> Australia    1990
> Australia    1991
> Australia    1992
> Australia    1993
> Australia    1994
> Australia    1995
>

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