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The above question appeared on Statalist. Here
is our reply:
Is there any direct way to save into a new variable the frequencies
obtained by applying the command tabulate?
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Title
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Saving frequencies produced by tabulate
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Author
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William Sribney, StataCorp
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Date
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March 1997; minor revisions September 2005
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There are three ways to put frequencies in a new variable:
- tabulate
will save counts as a matrix.
svmat can be used to create variables from the matrix.
- Use the
collapse
command. You may have to merge the resulting variables back with the
original dataset if you want to have them both together. The counts
are in a different form than (1)—you may or may not find this
desirable.
- Use
egen ... = count(1), by(...).
The counts are in a different form than (1) or (2)—you may or
may not find this desirable.
Below are some examples that use two by variables; you can also
use only one or more than two.
Example using tabulate
. sysuse auto, clear
(1978 Automobile Data)
. tab rep78 foreign, matcell(x)
Repair | Car type
Record 1978| Domestic Foreign | Total
-----------+----------------------+----------
1 | 2 0 | 2
2 | 8 0 | 8
3 | 27 3 | 30
4 | 9 9 | 18
5 | 2 9 | 11
-----------+----------------------+----------
Total | 48 21 | 69
. matrix list x
x[5,2]
c1 c2
r1 2 0
r2 8 0
r3 27 3
r4 9 9
r5 2 9
. svmat x
. list x* in 1/10
+---------+
| x1 x2 |
|---------|
1. | 2 0 |
2. | 8 0 |
3. | 27 3 |
4. | 9 9 |
5. | 2 9 |
|---------|
6. | . . |
7. | . . |
8. | . . |
9. | . . |
10. | . . |
+---------+
Example using collapse
. sysuse auto, clear
(1978 Automobile Data)
. gen x = 1
. collapse (count) x, by(rep78 foreign)
. list
+-----------------------+
| rep78 foreign x |
|-----------------------|
1. | 1 Domestic 2 |
2. | 2 Domestic 8 |
3. | 3 Domestic 27 |
4. | 3 Foreign 3 |
5. | 4 Domestic 9 |
|-----------------------|
6. | 4 Foreign 9 |
7. | 5 Domestic 2 |
8. | 5 Foreign 9 |
9. | . Domestic 4 |
10. | . Foreign 1 |
+-----------------------+
Notice that cells with 0 frequency are missing. That is,
rep78 foreign x
----- -------- ---
1 Domestic 2
1 Foreign 0 <-- this cell is not in dataset
2 Domestic 8
2 Foreign 0 <-- this cell is not in dataset
3 Domestic 27
3 Foreign 3
4 Domestic 9
4 Foreign 9
5 Domestic 2
5 Foreign 9
. Domestic 4
. Foreign 1
If you want to have the cells with 0 frequences in your dataset, you can do
so using the
fillin
command and a replace.
. sysuse auto, clear
. gen x = 1
. collapse (count) x, by(rep78 foreign)
. fillin rep78 foreign
. replace x = 0 if x==.
(2 real changes made)
. list
+---------------------------------+
| rep78 foreign x _fillin |
|---------------------------------|
1. | 1 Domestic 2 0 |
2. | 1 Foreign 0 1 |
3. | 2 Domestic 8 0 |
4. | 2 Foreign 0 1 |
5. | 3 Domestic 27 0 |
|---------------------------------|
6. | 3 Foreign 3 0 |
7. | 4 Domestic 9 0 |
8. | 4 Foreign 9 0 |
9. | 5 Domestic 2 0 |
10. | 5 Foreign 9 0 |
|---------------------------------|
11. | . Domestic 4 0 |
12. | . Foreign 1 0 |
+---------------------------------+
Example using egen
. sysuse auto, clear
(1978 Automobile Data)
. egen x = count(1), by(rep78 foreign)
. list rep78 foreign x
+-----------------------+
| rep78 foreign x |
|-----------------------|
1. | 3 Domestic 27 |
2. | 3 Domestic 27 |
3. | . Domestic 4 |
4. | 3 Domestic 27 |
5. | 4 Domestic 9 |
|-----------------------|
6. | 3 Domestic 27 |
7. | . Domestic 4 |
8. | 3 Domestic 27 |
9. | 3 Domestic 27 |
10. | 3 Domestic 27 |
|-----------------------|
11. | 3 Domestic 27 |
12. | 2 Domestic 8 |
13. | 3 Domestic 27 |
14. | 3 Domestic 27 |
15. | 4 Domestic 9 |
|-----------------------|
16. | 3 Domestic 27 |
17. | 2 Domestic 8 |
18. | 2 Domestic 8 |
19. | 3 Domestic 27 |
20. | 5 Domestic 2 |
|-----------------------|
21. | 2 Domestic 8 |
22. | 2 Domestic 8 |
23. | 2 Domestic 8 |
24. | 4 Domestic 9 |
25. | 3 Domestic 27 |
|-----------------------|
26. | 3 Domestic 27 |
27. | 3 Domestic 27 |
28. | 3 Domestic 27 |
29. | 4 Domestic 9 |
30. | 4 Domestic 9 |
|-----------------------|
31. | 3 Domestic 27 |
32. | 3 Domestic 27 |
33. | 4 Domestic 9 |
34. | 3 Domestic 27 |
35. | 4 Domestic 9 |
|-----------------------|
36. | 3 Domestic 27 |
37. | 3 Domestic 27 |
38. | 4 Domestic 9 |
39. | 3 Domestic 27 |
40. | 1 Domestic 2 |
|-----------------------|
41. | 3 Domestic 27 |
42. | 3 Domestic 27 |
43. | 5 Domestic 2 |
44. | 3 Domestic 27 |
45. | . Domestic 4 |
|-----------------------|
46. | 2 Domestic 8 |
47. | 4 Domestic 9 |
48. | 1 Domestic 2 |
49. | 3 Domestic 27 |
50. | 3 Domestic 27 |
|-----------------------|
51. | . Domestic 4 |
52. | 2 Domestic 8 |
53. | 5 Foreign 9 |
54. | 3 Foreign 3 |
55. | 4 Foreign 9 |
|-----------------------|
56. | 4 Foreign 9 |
57. | 5 Foreign 9 |
58. | 4 Foreign 9 |
59. | 4 Foreign 9 |
60. | 3 Foreign 3 |
|-----------------------|
61. | 5 Foreign 9 |
62. | 4 Foreign 9 |
63. | 4 Foreign 9 |
64. | . Foreign 1 |
65. | 3 Foreign 3 |
|-----------------------|
66. | 5 Foreign 9 |
67. | 5 Foreign 9 |
68. | 5 Foreign 9 |
69. | 5 Foreign 9 |
70. | 4 Foreign 9 |
|-----------------------|
71. | 5 Foreign 9 |
72. | 4 Foreign 9 |
73. | 4 Foreign 9 |
74. | 5 Foreign 9 |
+-----------------------+
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