exporting after "mean, over" command

[Khair Mrad]

exporting after "mean, over" command

hello everyone

I am having a hard time figuring out how to export my results of the means table as you see here:

. mean a170, over( time_period name )

Mean estimation Number of obs = 434,226

-------------------------------------------------------------------------------------
| Mean Std. err. [95% conf. interval]
------------------------------------+------------------------------------------------
c.a170@time_period#name |
1981-1984#United States of America | 7.728843 .0389972 7.65241 7.805276
1981-1984#Puerto Rico | 0 (no observations)
1981-1984#Canada | 7.874299 .0468632 7.782449 7.96615
1981-1984#Haiti | 0 (no observations)
1981-1984#Dominican Republic | 0 (no observations)
1981-1984#Trinidad and Tobago | 0 (no observations)
1981-1984#Mexico | 8.028338 .0393782 7.951158 8.105518

and the list goes on for thousands of results
thank you so much for your help

[Carlo Lazzaro]

Khair:
welcome to this forum.
Why not considering -statsby- (saving a copy of your original dataset before running it)?

use "https://www.stata-press.com/data/r17/nlswork.dta"
 statsby, by( idcode ), if idcode<=1000: mean ln_wage
      Command: mean ln_wage if idcode<=1000
           By: idcode

Statsby groups
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 
..................................................    50
..................................................   100
..................................................   150
..................................................   200
..................................................   250
..................................................   300
..................................................   350
..................................................   400
..................................................   450
..................................................   500
..................................................   550
..................................................   600
..................................................   650
..................................................   700
..................................................   750
..................................................   800
..................................................   850
...........................................

. list in 1/20

     +-------------------+
     | idcode   _b_ln_~e |
     |-------------------|
  1. |      1   2.040433 |
  2. |      2   1.688055 |
  3. |      3   1.584755 |
  4. |      4   1.994632 |
  5. |      5    1.84863 |
     |-------------------|
  6. |      6   1.790184 |
  7. |      7   1.365099 |
  8. |      9   2.063594 |
  9. |     10   1.326461 |
 10. |     12   2.923001 |
     |-------------------|
 11. |     13   2.241816 |
 12. |     14   2.095263 |
 13. |     15    2.48709 |
 14. |     16   2.140758 |
 15. |     17   2.182648 |
     |-------------------|
 16. |     18   1.515292 |
 17. |     19   1.983067 |
 18. |     20   2.086595 |
 19. |     21    1.84121 |
 20. |     22   2.149189 |
     +-------------------+

.

[Khair Mrad]

that worked perfectly
thank you so much