Transforming a dataset in a more compact format (Stata) - database

Question

initially I was dealing with a dataset that looked something like this:
+------+--------+-----------+-------+
| date | geo | variables | value |
+------+--------+-----------+-------+
| 1981 | Canada | var1 | # |
| 1982 | Canada | var1 | # |
| 1983 | Canada | var1 | # |
| ... | ... | ... | ... |
| 2015 | Canada | var2 | # |
| 1981 | Canada | var2 | # |
| 1982 | Canada | var2 | # |
| ... | ... | ... | ... |
| 2015 | Canada | var2 | # |
| 1981 | Quebec | var1 | # |
| 1982 | Quebec | var1 | # |
| 1983 | Quebec | var1 | # |
| ... | ... | ... | ... |
| 2015 | Quebec | var2 | # |
| 1981 | Quebec | var2 | # |
| 1982 | Quebec | var2 | # |
| ... | ... | ... | ... |
| 2015 | Quebec | var2 | # |
+------+--------+-----------+-------+
So I have 35 time periods, two countries and two variables. I would like to transform the table in Stata for it to look like this:
+------+--------+------+------+
| date | geo | var1 | var2 |
+------+--------+------+------+
| 1981 | Canada | # | # |
| 1982 | Canada | # | # |
| ... | ... | ... | ... |
| 2015 | Canada | # | # |
| 1981 | Quebec | # | # |
| 1982 | Quebec | # | # |
| ... | ... | ... | ... |
| 2015 | Quebec | # | # |
+------+--------+------+------+
However, I'm not having much success with this. I tried to separate the different observations into variables with the command:
separate value, by(variables) generate(var)
Which creates something like this:
+------+--------+------+------+
| date | geo | var1 | var2 |
+------+--------+------+------+
| 1981 | Canada | # | . |
| 1982 | Canada | # | . |
| ... | ... | ... | ... |
| 2015 | Canada | # | . |
| 1981 | Canada | . | # |
| 1982 | Canada | . | # |
| ... | ... | ... | ... |
| 2015 | Canada | . | # |
| 1981 | Quebec | # | . |
| 1982 | Quebec | # | . |
| ... | ... | ... | ... |
| 2015 | Quebec | # | . |
| 1981 | Quebec | . | # |
| 1982 | Quebec | . | # |
| ... | ... | ... | ... |
| 2015 | Quebec | . | # |
+------+--------+------+------+
Which contains a lot of useless missing values.
So, more specifically, I would like something to bring me directly to Table A to B (i.e. without using separate), or a solution to fix Table C into B.
Thanks a lot.

Answer 1

Without sample data, my answer will have to be untested. I think something like the following will get you started in the right direction.
reshape wide value, i(date geo) j(variables) string
Note that this assumes the contents of your variables variable are suitable for use as variable names. For example, a value of 1potato for variables would be a problem.
In any event,
help reshape
should be your first stop.
Added in response to comment: Here is some data I made up and a demonstration that reshape works for this data. Perhaps you can explain how this data differs from the real data. Your error message suggests that for some combination of date and geo, a particular value of variables occurs more than once.
. list, sepby(geo)
+----------------------------------+
| date geo variab~s value |
|----------------------------------|
1. | 1981 Canada var1 111 |
2. | 1982 Canada var1 211 |
3. | 1983 Canada var1 311 |
4. | 1981 Canada var2 112 |
5. | 1982 Canada var2 212 |
6. | 1983 Canada var2 312 |
|----------------------------------|
7. | 1981 Quebec var1 121 |
8. | 1982 Quebec var1 221 |
9. | 1983 Quebec var1 321 |
10. | 1981 Quebec var2 122 |
11. | 1982 Quebec var2 222 |
12. | 1983 Quebec var2 322 |
+----------------------------------+
. reshape wide value, i(geo date) j(variables) string
(note: j = var1 var2)
Data long -> wide
-----------------------------------------------------------------------------
Number of obs. 12 -> 6
Number of variables 4 -> 4
j variable (2 values) variables -> (dropped)
xij variables:
value -> valuevar1 valuevar2
-----------------------------------------------------------------------------
. rename (value*) (*)
. list, sepby(geo)
+-----------------------------+
| date geo var1 var2 |
|-----------------------------|
1. | 1981 Canada 111 112 |
2. | 1982 Canada 211 212 |
3. | 1983 Canada 311 312 |
|-----------------------------|
4. | 1981 Quebec 121 122 |
5. | 1982 Quebec 221 222 |
6. | 1983 Quebec 321 322 |
+-----------------------------+
.