As often, -reshape long- makes life easier. Try out:
. reshape long d, i(id) j(station)
. by id (d), sort: gen min_dis_new = d[2]
. by id (d), sort: gen min_dis_id = station[2]
which also is a neat way to produce "min_dis". You might than use -reshape
wide- to get back your original data structure, but I bet that you are better
of with long. See -help reshape- for details.
many regards
Uli
Jitian Sheu wrote:
> Dear listers:
>
> I have a data set with the following structure:
>
> id d1 d2 d3..... d2500 min_dis
> 1 0 23 21 530 21
> 2 23 0
> 3
> 4
> 5
> ...
> (up to 2500)
>
> i.e. number of observation=2500, and each one represent to one station(id)
> dX= the distance to stationX, X=1...2500
> (since there are 2500 observation,==> I have 2500 distance variables)
>
> min_dis=minimum distance of the nearest station.
>
>
> So, for each observation(station), I know its minimum distance to another
> station.
> Now, I want to know its nearest station id.
> i.e. I want to have another variable (say called near_id). By this new
> variable, I can then obtain the id number of each observation's nearest
> station id.
>
> For example (using the above data)
>
> id d1 d2 d3..... d2500 min_dis ==> near_id
> 1 0 23 29 530 21 ==> 2
> 2 23 0 32 41 23 ==> 1
> 3 29 32 0 52 21 ==> 2
> 4
> 5
> ...
>
> For this purpose, I use the following programming code.
> Basically, I am doing this observation by observation:
>
> gen near_id=.
>
> forvalues i=1(1)2500{
>
> forvalues j=1(1)2500{
> replace near_id =`j' if id==`i'&
> d`j'==min_dis
>
> }
> }
>
> Therefore, there are totally 2500X2500 loops
> If each loop takes 2 seconds==> totally, I need 5000 seconds to finish the
> whole process, which is 1.4 hours.
>
> Is there any efficient way to do that?
>
> Many thanks.
>
> JT
>
>
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