Emanuele, does -isid regio- return an error? The -isid- command will
verify if you have wide data.
Anders Alexandersson
[email protected]
Emanuele Millemaci <[email protected]> wrote:
> Ada,
>
> I tried two different ways to read in the data obtaining the same
> disappointing results: 1)I used the command "insheet" 2) I copied
> from excel and pasted into the data editor. Data look rectangular and
> I cannot see missing values before typing the reshape command.
>
>
> 2008/12/9 Ada Ma <[email protected]>:
>> Emanuele,
>>
>> Have you read in the data correctly? If the data isn't read in
>> correctly then it may not form a proper rectangle, which explains why
>> it doesn't -reshape- properly.
>>
>> Ada
>>
>>
>> On Tue, Dec 9, 2008 at 1:41 PM, Martin Weiss <[email protected]> wrote:
>>> Sounds like a http://www.stata.com/statalist/archive/2005-11/msg01084.html
>>> problem... Where should the randomness come from in a command like
>>> -reshape-?
>>>
>>> HTH
>>> Martin
>>>
>>>
>>> -----Original Message-----
>>> From: [email protected]
>>> [mailto:[email protected]] On Behalf Of Emanuele
>>> Millemaci
>>> Sent: Tuesday, December 09, 2008 1:27 PM
>>> To: [email protected]
>>> Subject: st: reshape problem
>>>
>>> Hi,
>>>
>>> I had a dataset on excel with regions on the rows and years on the columns.
>>> I moved this data to Stata 10.1 MP(updated to the latest packages) and
>>> was trying to reshaping from wide to long as I would like to have all
>>> years' data of the same variable on the same column.
>>>
>>> Below, I report an example of what I have:
>>>
>>> regio prod1995 prod1996 .....prod2006
>>>
>>> 1 .... ... ...
>>> 2 ... ... ...
>>> 3 ... ... ...
>>> 4 ... ... ...
>>>
>>> I would like to get:
>>>
>>> regio years prod
>>> 1 1995 ...
>>> 1 1996 ...
>>> ..
>>> 2 1995 ...
>>> ..
>>> 3 1995 ...
>>> ..
>>> 4 1995 ...
>>> ..
>>>
>>> The command I use is:
>>>
>>> reshape long prod, i(regio) j(year)
>>>
>>> It would appear a very easy task. Instead, the result I get is always
>>> different (every time I launch the command) and never correct.
>>> Stata drops many observations and many others become missing for some
>>> variable (whereas my dataset has no missing value). I have also
>>> checked that Stata considers data as numeric.
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