The theme that you may need two -reshape-s is ventilated with examples
within
FAQ . . . . . . . . . . . . . . . . . . . . . . . . Problems with
reshape
12/03 I am having problems with the reshape command. Can
you give further guidance?
http://www.stata.com/support/faqs/data/reshape3.html
An alternative to Phil's
. ren yrGDP GDP
. ren yrPopulation Population
is just
. renpfix yr
The saving would be greater in a more extensive example with more
variables.
Nick
[email protected]
Phil Schumm
On Apr 7, 2008, at 9:27 PM, Glenn Hoetker wrote:
> The data is in this layout (with fictional data)
>
> COUNTRY DATA_SERIES YR1960 YR1961 YR1962
> Argentina GDP 5 7 9
> Argentina Population 10 8 5
> Brazil GDP 1 9 10
> Brazil Population 5 35 12
>
> I would like to get it into this format:
>
> COUNTRY YEAR GDP POPULATION
> Argentina 1960 5 10
> Argentina 1961 7 8
> ...
> Brazil 1960 1 5
> Brazil 1961 9 35
> etc.
The trick in this case is to go "fully long" and then come back to
wide (but WRT the data series dimension rather than the time dimension):
. li
+---------------------------------------------------+
| country data_ser~s yr1960 yr1961 yr1962 |
|---------------------------------------------------|
1. | Argentina GDP 5 7 9 |
2. | Argentina Population 10 8 5 |
3. | Brazil GDP 1 9 10 |
4. | Brazil Population 5 35 12 |
+---------------------------------------------------+
. reshape long yr, i(country data_series) j(year)
<output omitted>
. reshape wide yr, i(country year) j(data_series) string
<output omitted>
. ren yrGDP GDP
. ren yrPopulation Population
. li
+-----------------------------------+
| country year GDP Popula~n |
|-----------------------------------|
1. | Argentina 1960 5 10 |
2. | Argentina 1961 7 8 |
3. | Argentina 1962 9 5 |
4. | Brazil 1960 1 5 |
5. | Brazil 1961 9 35 |
|-----------------------------------|
6. | Brazil 1962 10 12 |
+-----------------------------------+
The general principle here is to start by making your data as long as
possible; from that point, it's usually easier to see how to get to
where you want to go. Note that the code above assumes that
data_series is a string variable; if not, you'll need to make
appropriate adjustments.
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