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Re: st: Doubts on how to better prepare my dataset with -reshape- and -merge_


From   Clarice Martins <[email protected]>
To   [email protected]
Subject   Re: st: Doubts on how to better prepare my dataset with -reshape- and -merge_
Date   Mon, 28 Oct 2013 14:07:34 -0200

Thank you Roberto!

It worked perfectly...

Thanks!


On Oct 28, 2013, at 1:05 AM, Roberto Ferrer wrote:

> Try the -string- option with -reshape- . No need to rename (with your
> example, at least):
> 
> *---------------------------- begin code
> --------------------------------------------
> clear
> input co_id str4 ticker_name str9 return_type returnJun2000
> returnJul2000 returnAug2000
> 1 ABCB formation 0.01 0.2 0.3
> 2 AEDU formation 0.01 0.2 0.3
> 3 AMBV formation 0.01 0.2 0.3
> 1 ABCB buysell 0.01 0.2 0.3
> 2 AEDU buysell 0.01 0.2 0.3
> 3 AMBV buysell 0.01 0.2 0.3
> 1 ABCB holding 0.01 0.2 0.3
> 2 AEDU holding 0.01 0.2 0.3
> 3 AMBV holding 0.01 0.2 0.3
> end
> 
> 
> rename return_type rtype
> 
> reshape long return, i(co_id rtype) j(yrmonth) string
> 
> order ticker_name, after(co_id)
> sort co_id rtype
> list, noobs sepby(co_id rtype) abbrev(14)
> 
> 
> *-------------------------------- end code
> -------------------------------------------
> 
> On Sun, Oct 27, 2013 at 9:47 PM, Clarice Martins
> <[email protected]> wrote:
>> Red Owl, thank you!
>> 
>> I see your point, and it sounds it will work.
>> 
>> The only question is: i do have 151 return periods to type up year and month... is there another way?
>> 
>>> rename returnJun2000 return200006
>>> rename returnJul2000 return200007
>>> rename returnAug2000 return200008
>> 
>> 
>> 
>> 
>> 
>> On Oct 27, 2013, at 6:09 PM, Red Owl wrote:
>> 
>>> Clarice,
>>> 
>>> I am not sure I understand what you want, but perhaps this will
>>> do it or give you a conceptual approach:
>>> 
>>> clear
>>> input co_id str4 ticker_name str9 return_type returnJun2000
>>> returnJul2000 returnAug2000
>>> 1 ABCB formation 0.01 0.2 0.3
>>> 2 AEDU formation 0.01 0.2 0.3
>>> 3 AMBV formation 0.01 0.2 0.3
>>> 1 ABCB buysell 0.01 0.2 0.3
>>> 2 AEDU buysell 0.01 0.2 0.3
>>> 3 AMBV buysell 0.01 0.2 0.3
>>> 1 ABCB holding 0.01 0.2 0.3
>>> 2 AEDU holding 0.01 0.2 0.3
>>> 3 AMBV holding 0.01 0.2 0.3
>>> end
>>> 
>>> rename return_type rtype
>>> rename returnJun2000 return200006
>>> rename returnJul2000 return200007
>>> rename returnAug2000 return200008
>>> 
>>> reshape long return, i(co_id rtype) j(yrmonth)
>>> 
>>> order ticker_name, after(co_id)
>>> sort co_id rtype
>>> list, noobs sepby(co_id rtype) abbrev(14)
>>> 
>>> 
>>> Red Owl
>>> [email protected]
>>> 
>>> 
>>>>> 
>>>>> Clarice Martins wrote:
>>> 
>>> I have:
>>> - dataset that is wide
>>> - i couldn't figure out how to transform it to long using -reshape-
>>> because there is 3 variables that uniquely define an observation: co_id
>>> (an id per company), period (a month and year period for each
>>> observation), and type_return (there are 3 different types of return and
>>> for each there is an observation per company, per period)
>>> - dataset looks like this:
>>> 
>>> co_id ticker_name return_type returnJun2000 returnJul2000 returnAug2000
>>> (and so on)
>>> 1 ABCB formation 0.01 0.2 0.3
>>> 2 AEDU formation 0.01 0.2 0.3
>>> 3 AMBV formation 0.01 0.2 0.3
>>> 1 ABCB buysell 0.01 0.2 0.3
>>> 2 AEDU buysell 0.01 0.2 0.3
>>> 3 AMBV buysell 0.01 0.2 0.3
>>> 1 ABCB holding 0.01 0.2 0.3
>>> 2 AEDU holding 0.01 0.2 0.3
>>> 3 AMBV holding 0.01 0.2 0.3
>>> *
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>>> *   http://www.ats.ucla.edu/stat/stata/
>> 
>> 
>> *
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