sum计算统计量（detail查看百分位数和阶段最值等）
-
Skewness：偏度（偏态系数），小于0表示左偏，即数据位于均值左边的比较少，大于0相反。绝对值越大，偏离程度越大。
-
Kurtosis：峰度（峰态系数），反映分布形态的陡峭程度，峰度越大，数据分布峰部形状越尖。
gen生成新变量
replace更改变量值
preserve—restore
-
preserve后可修改数据
-
restore后恢复原数据
-
相当于备份？
. sysuse auto, clear
(1978 automobile data)
. sum price, detail
Price
-------------------------------------------------------------
Percentiles Smallest
1% 3291 3291
5% 3748 3299
10% 3895 3667 Obs 74
25% 4195 3748 Sum of wgt. 74
50% 5006.5 Mean 6165.257
Largest Std. dev. 2949.496
75% 6342 13466
90% 11385 13594 Variance 8699526
95% 13466 14500 Skewness 1.653434
99% 15906 15906 Kurtosis 4.819188
. sum price
Variable | Obs Mean Std. dev. Min Max
-------------+---------------------------------------------------------
price | 74 6165.257 2949.496 3291 15906
. sysuse auto, clear
(1978 automobile data)
. by foreign: sum price weight
-------------------------------------------------------------------------------
-> foreign = Domestic
Variable | Obs Mean Std. dev. Min Max
-------------+---------------------------------------------------------
price | 52 6072.423 3097.104 3291 15906
weight | 52 3317.115 695.3637 1800 4840
-------------------------------------------------------------------------------
-> foreign = Foreign
Variable | Obs Mean Std. dev. Min Max
-------------+---------------------------------------------------------
price | 22 6384.682 2621.915 3748 12990
weight | 22 2315.909 433.0035 1760 3420
. by foreign: sum price weight length if price > 5000, detail
-------------------------------------------------------------------------------
-> foreign = Domestic
Price
-------------------------------------------------------------
Percentiles Smallest
1% 5104 5104
5% 5172 5172
10% 5189 5189 Obs 23
25% 5705 5222 Sum of wgt. 23
50% 6342 Mean 8359.609
Largest Std. dev. 3491.661
75% 11385 13466
90% 13594 13594 Variance 1.22e+07
95% 14500 14500 Skewness .8240605
99% 15906 15906 Kurtosis 2.252418
Weight (lbs.)
-------------------------------------------------------------
Percentiles Smallest
1% 2520 2520
5% 3210 3210
10% 3220 3220 Obs 23
25% 3600 3280 Sum of wgt. 23
50% 3830 Mean 3817.826
Largest Std. dev. 511.5392
75% 4080 4290
90% 4330 4330 Variance 261672.3
95% 4720 4720 Skewness -.2778813
99% 4840 4840 Kurtosis 3.574592
Length (in.)
-------------------------------------------------------------
Percentiles Smallest
1% 182 182
5% 198 198
10% 200 200 Obs 23
25% 201 200 Sum of wgt. 23
50% 212 Mean 210.8261
Largest Std. dev. 11.75373
75% 220 221
90% 222 222 Variance 138.1502
95% 230 230 Skewness -.2226277
99% 233 233 Kurtosis 2.991821
-------------------------------------------------------------------------------
-> foreign = Foreign
Price
-------------------------------------------------------------
Percentiles Smallest
1% 5079 5079
5% 5079 5397
10% 5397 5719 Obs 14
25% 5799 5799 Sum of wgt. 14
50% 6572.5 Mean 7639
Largest Std. dev. 2523.636
75% 9690 9690
90% 11995 9735 Variance 6368737
95% 12990 11995 Skewness 1.000074
99% 12990 12990 Kurtosis 2.710336
Weight (lbs.)
-------------------------------------------------------------
Percentiles Smallest
1% 1990 1990
5% 1990 2040
10% 2040 2070 Obs 14
25% 2160 2160 Sum of wgt. 14
50% 2390 Mean 2503.571
Largest Std. dev. 432.4458
75% 2750 2750
90% 3170 2830 Variance 187009.3
95% 3420 3170 Skewness .7238332
99% 3420 3420 Kurtosis 2.585679
Length (in.)
-------------------------------------------------------------
Percentiles Smallest
1% 155 155
5% 155 156
10% 156 170 Obs 14
25% 170 170 Sum of wgt. 14
50% 174 Mean 175.2143
Largest Std. dev. 11.51707
75% 184 184
90% 192 189 Variance 132.6429
95% 193 192 Skewness -.106999
99% 193 193 Kurtosis 2.478998
. sum foreign
Variable | Obs Mean Std. dev. Min Max
-------------+---------------------------------------------------------
foreign | 74 .2972973 .4601885 0 1
. sum foreign, detail
Car origin
-------------------------------------------------------------
Percentiles Smallest
1% 0 0
5% 0 0
10% 0 0 Obs 74
25% 0 0 Sum of wgt. 74
50% 0 Mean .2972973
Largest Std. dev. .4601885
75% 1 1
90% 1 1 Variance .2117734
95% 1 1 Skewness .8869686
99% 1 1 Kurtosis 1.786713
. generate price2 = price + 15
. list price price2
+-----------------+
| price price2 |
|-----------------|
1. | 4,099 4114 |
2. | 4,749 4764 |
3. | 3,799 3814 |
4. | 4,816 4831 |
5. | 7,827 7842 |
|-----------------|
6. | 5,788 5803 |
7. | 4,453 4468 |
8. | 5,189 5204 |
9. | 10,372 10387 |
10. | 4,082 4097 |
|-----------------|
11. | 11,385 11400 |
12. | 14,500 14515 |
13. | 15,906 15921 |
14. | 3,299 3314 |
15. | 5,705 5720 |
|-----------------|
16. | 4,504 4519 |
17. | 5,104 5119 |
18. | 3,667 3682 |
19. | 3,955 3970 |
20. | 3,984 3999 |
|-----------------|
21. | 4,010 4025 |
22. | 5,886 5901 |
23. | 6,342 6357 |
24. | 4,389 4404 |
25. | 4,187 4202 |
|-----------------|
26. | 11,497 11512 |
27. | 13,594 13609 |
28. | 13,466 13481 |
29. | 3,829 3844 |
30. | 5,379 5394 |
|-----------------|
31. | 6,165 6180 |
32. | 4,516 4531 |
33. | 6,303 6318 |
34. | 3,291 3306 |
35. | 8,814 8829 |
|-----------------|
36. | 5,172 5187 |
37. | 4,733 4748 |
38. | 4,890 4905 |
39. | 4,181 4196 |
40. | 4,195 4210 |
|-----------------|
41. | 10,371 10386 |
42. | 4,647 4662 |
43. | 4,425 4440 |
44. | 4,482 4497 |
45. | 6,486 6501 |
|-----------------|
46. | 4,060 4075 |
47. | 5,798 5813 |
48. | 4,934 4949 |
49. | 5,222 5237 |
50. | 4,723 4738 |
|-----------------|
51. | 4,424 4439 |
52. | 4,172 4187 |
53. | 9,690 9705 |
54. | 6,295 6310 |
55. | 9,735 9750 |
|-----------------|
56. | 6,229 6244 |
57. | 4,589 4604 |
58. | 5,079 5094 |
59. | 8,129 8144 |
60. | 4,296 4311 |
|-----------------|
61. | 5,799 5814 |
62. | 4,499 4514 |
63. | 3,995 4010 |
64. | 12,990 13005 |
65. | 3,895 3910 |
|-----------------|
66. | 3,798 3813 |
67. | 5,899 5914 |
68. | 3,748 3763 |
69. | 5,719 5734 |
70. | 7,140 7155 |
|-----------------|
71. | 5,397 5412 |
72. | 4,697 4712 |
73. | 6,850 6865 |
74. | 11,995 12010 |
+-----------------+
. replace price2 = price2 - 15
(74 real changes made)
. list price price2
+-----------------+
| price price2 |
|-----------------|
1. | 4,099 4099 |
2. | 4,749 4749 |
3. | 3,799 3799 |
4. | 4,816 4816 |
5. | 7,827 7827 |
|-----------------|
6. | 5,788 5788 |
7. | 4,453 4453 |
8. | 5,189 5189 |
9. | 10,372 10372 |
10. | 4,082 4082 |
|-----------------|
11. | 11,385 11385 |
12. | 14,500 14500 |
13. | 15,906 15906 |
14. | 3,299 3299 |
15. | 5,705 5705 |
|-----------------|
16. | 4,504 4504 |
17. | 5,104 5104 |
18. | 3,667 3667 |
19. | 3,955 3955 |
20. | 3,984 3984 |
|-----------------|
21. | 4,010 4010 |
22. | 5,886 5886 |
23. | 6,342 6342 |
24. | 4,389 4389 |
25. | 4,187 4187 |
|-----------------|
26. | 11,497 11497 |
27. | 13,594 13594 |
28. | 13,466 13466 |
29. | 3,829 3829 |
30. | 5,379 5379 |
|-----------------|
31. | 6,165 6165 |
32. | 4,516 4516 |
33. | 6,303 6303 |
34. | 3,291 3291 |
35. | 8,814 8814 |
|-----------------|
36. | 5,172 5172 |
37. | 4,733 4733 |
38. | 4,890 4890 |
39. | 4,181 4181 |
40. | 4,195 4195 |
|-----------------|
41. | 10,371 10371 |
42. | 4,647 4647 |
43. | 4,425 4425 |
44. | 4,482 4482 |
45. | 6,486 6486 |
|-----------------|
46. | 4,060 4060 |
47. | 5,798 5798 |
48. | 4,934 4934 |
49. | 5,222 5222 |
50. | 4,723 4723 |
|-----------------|
51. | 4,424 4424 |
52. | 4,172 4172 |
53. | 9,690 9690 |
54. | 6,295 6295 |
55. | 9,735 9735 |
|-----------------|
56. | 6,229 6229 |
57. | 4,589 4589 |
58. | 5,079 5079 |
59. | 8,129 8129 |
60. | 4,296 4296 |
|-----------------|
61. | 5,799 5799 |
62. | 4,499 4499 |
63. | 3,995 3995 |
64. | 12,990 12990 |
65. | 3,895 3895 |
|-----------------|
66. | 3,798 3798 |
67. | 5,899 5899 |
68. | 3,748 3748 |
69. | 5,719 5719 |
70. | 7,140 7140 |
|-----------------|
71. | 5,397 5397 |
72. | 4,697 4697 |
73. | 6,850 6850 |
74. | 11,995 11995 |
+-----------------+
. gen v1 = price^2
. list price v1
+-------------------+
| price v1 |
|-------------------|
1. | 4,099 1.68e+07 |
2. | 4,749 2.26e+07 |
3. | 3,799 1.44e+07 |
4. | 4,816 2.32e+07 |
5. | 7,827 6.13e+07 |
|-------------------|
6. | 5,788 3.35e+07 |
7. | 4,453 1.98e+07 |
8. | 5,189 2.69e+07 |
9. | 10,372 1.08e+08 |
10. | 4,082 1.67e+07 |
|-------------------|
11. | 11,385 1.30e+08 |
12. | 14,500 2.10e+08 |
13. | 15,906 2.53e+08 |
14. | 3,299 1.09e+07 |
15. | 5,705 3.25e+07 |
|-------------------|
16. | 4,504 2.03e+07 |
17. | 5,104 2.61e+07 |
18. | 3,667 1.34e+07 |
19. | 3,955 1.56e+07 |
20. | 3,984 1.59e+07 |
|-------------------|
21. | 4,010 1.61e+07 |
22. | 5,886 3.46e+07 |
23. | 6,342 4.02e+07 |
24. | 4,389 1.93e+07 |
25. | 4,187 1.75e+07 |
|-------------------|
26. | 11,497 1.32e+08 |
27. | 13,594 1.85e+08 |
28. | 13,466 1.81e+08 |
29. | 3,829 1.47e+07 |
30. | 5,379 2.89e+07 |
|-------------------|
31. | 6,165 3.80e+07 |
32. | 4,516 2.04e+07 |
33. | 6,303 3.97e+07 |
34. | 3,291 1.08e+07 |
35. | 8,814 7.77e+07 |
|-------------------|
36. | 5,172 2.67e+07 |
37. | 4,733 2.24e+07 |
38. | 4,890 2.39e+07 |
39. | 4,181 1.75e+07 |
40. | 4,195 1.76e+07 |
|-------------------|
41. | 10,371 1.08e+08 |
42. | 4,647 2.16e+07 |
43. | 4,425 1.96e+07 |
44. | 4,482 2.01e+07 |
45. | 6,486 4.21e+07 |
|-------------------|
46. | 4,060 1.65e+07 |
47. | 5,798 3.36e+07 |
48. | 4,934 2.43e+07 |
49. | 5,222 2.73e+07 |
50. | 4,723 2.23e+07 |
|-------------------|
51. | 4,424 1.96e+07 |
52. | 4,172 1.74e+07 |
53. | 9,690 9.39e+07 |
54. | 6,295 3.96e+07 |
55. | 9,735 9.48e+07 |
|-------------------|
56. | 6,229 3.88e+07 |
57. | 4,589 2.11e+07 |
58. | 5,079 2.58e+07 |
59. | 8,129 6.61e+07 |
60. | 4,296 1.85e+07 |
|-------------------|
61. | 5,799 3.36e+07 |
62. | 4,499 2.02e+07 |
63. | 3,995 1.60e+07 |
64. | 12,990 1.69e+08 |
65. | 3,895 1.52e+07 |
|-------------------|
66. | 3,798 1.44e+07 |
67. | 5,899 3.48e+07 |
68. | 3,748 1.40e+07 |
69. | 5,719 3.27e+07 |
70. | 7,140 5.10e+07 |
|-------------------|
71. | 5,397 2.91e+07 |
72. | 4,697 2.21e+07 |
73. | 6,850 4.69e+07 |
74. | 11,995 1.44e+08 |
+-------------------+
. gen v2 = price^3
. gen v3 = price^0.5
. list v1-v3
+--------------------------------+
| v1 v2 v3 |
|--------------------------------|
1. | 1.68e+07 6.89e+10 64.02343 |
2. | 2.26e+07 1.07e+11 68.91299 |
3. | 1.44e+07 5.48e+10 61.63603 |
4. | 2.32e+07 1.12e+11 69.39741 |
5. | 6.13e+07 4.79e+11 88.47034 |
|--------------------------------|
6. | 3.35e+07 1.94e+11 76.0789 |
7. | 1.98e+07 8.83e+10 66.7308 |
8. | 2.69e+07 1.40e+11 72.03471 |
9. | 1.08e+08 1.12e+12 101.843 |
10. | 1.67e+07 6.80e+10 63.89053 |
|--------------------------------|
11. | 1.30e+08 1.48e+12 106.7005 |
12. | 2.10e+08 3.05e+12 120.4159 |
13. | 2.53e+08 4.02e+12 126.119 |
14. | 1.09e+07 3.59e+10 57.43692 |
15. | 3.25e+07 1.86e+11 75.53145 |
|--------------------------------|
16. | 2.03e+07 9.14e+10 67.11185 |
17. | 2.61e+07 1.33e+11 71.44228 |
18. | 1.34e+07 4.93e+10 60.55576 |
19. | 1.56e+07 6.19e+10 62.88879 |
20. | 1.59e+07 6.32e+10 63.11893 |
|--------------------------------|
21. | 1.61e+07 6.45e+10 63.32456 |
22. | 3.46e+07 2.04e+11 76.72027 |
23. | 4.02e+07 2.55e+11 79.63667 |
24. | 1.93e+07 8.45e+10 66.24953 |
25. | 1.75e+07 7.34e+10 64.70703 |
|--------------------------------|
26. | 1.32e+08 1.52e+12 107.2241 |
27. | 1.85e+08 2.51e+12 116.5933 |
28. | 1.81e+08 2.44e+12 116.0431 |
29. | 1.47e+07 5.61e+10 61.87891 |
30. | 2.89e+07 1.56e+11 73.34167 |
|--------------------------------|
31. | 3.80e+07 2.34e+11 78.51752 |
32. | 2.04e+07 9.21e+10 67.20119 |
33. | 3.97e+07 2.50e+11 79.39143 |
34. | 1.08e+07 3.56e+10 57.36724 |
35. | 7.77e+07 6.85e+11 93.8829 |
|--------------------------------|
36. | 2.67e+07 1.38e+11 71.91662 |
37. | 2.24e+07 1.06e+11 68.7968 |
38. | 2.39e+07 1.17e+11 69.92854 |
39. | 1.75e+07 7.31e+10 64.66065 |
40. | 1.76e+07 7.38e+10 64.76882 |
|--------------------------------|
41. | 1.08e+08 1.12e+12 101.8381 |
42. | 2.16e+07 1.00e+11 68.16891 |
43. | 1.96e+07 8.66e+10 66.52068 |
44. | 2.01e+07 9.00e+10 66.94774 |
45. | 4.21e+07 2.73e+11 80.53571 |
|--------------------------------|
46. | 1.65e+07 6.69e+10 63.71813 |
47. | 3.36e+07 1.95e+11 76.1446 |
48. | 2.43e+07 1.20e+11 70.24244 |
49. | 2.73e+07 1.42e+11 72.2634 |
50. | 2.23e+07 1.05e+11 68.72408 |
|--------------------------------|
51. | 1.96e+07 8.66e+10 66.51315 |
52. | 1.74e+07 7.26e+10 64.59102 |
53. | 9.39e+07 9.10e+11 98.4378 |
54. | 3.96e+07 2.49e+11 79.34103 |
55. | 9.48e+07 9.23e+11 98.66611 |
|--------------------------------|
56. | 3.88e+07 2.42e+11 78.92401 |
57. | 2.11e+07 9.66e+10 67.74216 |
58. | 2.58e+07 1.31e+11 71.26711 |
59. | 6.61e+07 5.37e+11 90.16096 |
60. | 1.85e+07 7.93e+10 65.54388 |
|--------------------------------|
61. | 3.36e+07 1.95e+11 76.15117 |
62. | 2.02e+07 9.11e+10 67.07458 |
63. | 1.60e+07 6.38e+10 63.20601 |
64. | 1.69e+08 2.19e+12 113.9737 |
65. | 1.52e+07 5.91e+10 62.40993 |
|--------------------------------|
66. | 1.44e+07 5.48e+10 61.62791 |
67. | 3.48e+07 2.05e+11 76.80495 |
68. | 1.40e+07 5.27e+10 61.22091 |
69. | 3.27e+07 1.87e+11 75.62407 |
70. | 5.10e+07 3.64e+11 84.49852 |
|--------------------------------|
71. | 2.91e+07 1.57e+11 73.46428 |
72. | 2.21e+07 1.04e+11 68.53466 |
73. | 4.69e+07 3.21e+11 82.76472 |
74. | 1.44e+08 1.73e+12 109.5217 |
+--------------------------------+
. sum v1-v3
Variable | Obs Mean Std. dev. Min Max
-------------+---------------------------------------------------------
v1 | 74 4.66e+07 5.14e+07 1.08e+07 2.53e+08
v2 | 74 4.35e+11 7.63e+11 3.56e+10 4.02e+12
v3 | 74 76.75214 16.67704 57.36724 126.119
. sum v1-v3, detail
-------------------------------------------------------------
Percentiles Smallest
1% 1.08e+07 1.08e+07
5% 1.40e+07 1.09e+07
10% 1.52e+07 1.34e+07 Obs 74
25% 1.76e+07 1.40e+07 Sum of wgt. 74
50% 2.51e+07 Mean 4.66e+07
Largest Std. dev. 5.14e+07
75% 4.02e+07 1.81e+08
90% 1.30e+08 1.85e+08 Variance 2.65e+15
95% 1.81e+08 2.10e+08 Skewness 2.224265
99% 2.53e+08 2.53e+08 Kurtosis 7.346822
-------------------------------------------------------------
Percentiles Smallest
1% 3.56e+10 3.56e+10
5% 5.27e+10 3.59e+10
10% 5.91e+10 4.93e+10 Obs 74
25% 7.38e+10 5.27e+10 Sum of wgt. 74
50% 1.26e+11 Mean 4.35e+11
Largest Std. dev. 7.63e+11
75% 2.55e+11 2.44e+12
90% 1.48e+12 2.51e+12 Variance 5.82e+23
95% 2.44e+12 3.05e+12 Skewness 2.797291
99% 4.02e+12 4.02e+12 Kurtosis 10.81449
-------------------------------------------------------------
Percentiles Smallest
1% 57.36724 57.36724
5% 61.22091 57.43692
10% 62.40993 60.55576 Obs 74
25% 64.76882 61.22091 Sum of wgt. 74
50% 70.75477 Mean 76.75214
Largest Std. dev. 16.67704
75% 79.63667 116.0431
90% 106.7005 116.5933 Variance 278.1238
95% 116.0431 120.4159 Skewness 1.361583
99% 126.119 126.119 Kurtosis 3.885685
. by foreign: list v1-v3
-------------------------------------------------------------------------------
-> foreign = Domestic
+--------------------------------+
| v1 v2 v3 |
|--------------------------------|
1. | 1.68e+07 6.89e+10 64.02343 |
2. | 2.26e+07 1.07e+11 68.91299 |
3. | 1.44e+07 5.48e+10 61.63603 |
4. | 2.32e+07 1.12e+11 69.39741 |
5. | 6.13e+07 4.79e+11 88.47034 |
|--------------------------------|
6. | 3.35e+07 1.94e+11 76.0789 |
7. | 1.98e+07 8.83e+10 66.7308 |
8. | 2.69e+07 1.40e+11 72.03471 |
9. | 1.08e+08 1.12e+12 101.843 |
10. | 1.67e+07 6.80e+10 63.89053 |
|--------------------------------|
11. | 1.30e+08 1.48e+12 106.7005 |
12. | 2.10e+08 3.05e+12 120.4159 |
13. | 2.53e+08 4.02e+12 126.119 |
14. | 1.09e+07 3.59e+10 57.43692 |
15. | 3.25e+07 1.86e+11 75.53145 |
|--------------------------------|
16. | 2.03e+07 9.14e+10 67.11185 |
17. | 2.61e+07 1.33e+11 71.44228 |
18. | 1.34e+07 4.93e+10 60.55576 |
19. | 1.56e+07 6.19e+10 62.88879 |
20. | 1.59e+07 6.32e+10 63.11893 |
|--------------------------------|
21. | 1.61e+07 6.45e+10 63.32456 |
22. | 3.46e+07 2.04e+11 76.72027 |
23. | 4.02e+07 2.55e+11 79.63667 |
24. | 1.93e+07 8.45e+10 66.24953 |
25. | 1.75e+07 7.34e+10 64.70703 |
|--------------------------------|
26. | 1.32e+08 1.52e+12 107.2241 |
27. | 1.85e+08 2.51e+12 116.5933 |
28. | 1.81e+08 2.44e+12 116.0431 |
29. | 1.47e+07 5.61e+10 61.87891 |
30. | 2.89e+07 1.56e+11 73.34167 |
|--------------------------------|
31. | 3.80e+07 2.34e+11 78.51752 |
32. | 2.04e+07 9.21e+10 67.20119 |
33. | 3.97e+07 2.50e+11 79.39143 |
34. | 1.08e+07 3.56e+10 57.36724 |
35. | 7.77e+07 6.85e+11 93.8829 |
|--------------------------------|
36. | 2.67e+07 1.38e+11 71.91662 |
37. | 2.24e+07 1.06e+11 68.7968 |
38. | 2.39e+07 1.17e+11 69.92854 |
39. | 1.75e+07 7.31e+10 64.66065 |
40. | 1.76e+07 7.38e+10 64.76882 |
|--------------------------------|
41. | 1.08e+08 1.12e+12 101.8381 |
42. | 2.16e+07 1.00e+11 68.16891 |
43. | 1.96e+07 8.66e+10 66.52068 |
44. | 2.01e+07 9.00e+10 66.94774 |
45. | 4.21e+07 2.73e+11 80.53571 |
|--------------------------------|
46. | 1.65e+07 6.69e+10 63.71813 |
47. | 3.36e+07 1.95e+11 76.1446 |
48. | 2.43e+07 1.20e+11 70.24244 |
49. | 2.73e+07 1.42e+11 72.2634 |
50. | 2.23e+07 1.05e+11 68.72408 |
|--------------------------------|
51. | 1.96e+07 8.66e+10 66.51315 |
52. | 1.74e+07 7.26e+10 64.59102 |
+--------------------------------+
-------------------------------------------------------------------------------
-> foreign = Foreign
+--------------------------------+
| v1 v2 v3 |
|--------------------------------|
1. | 9.39e+07 9.10e+11 98.4378 |
2. | 3.96e+07 2.49e+11 79.34103 |
3. | 9.48e+07 9.23e+11 98.66611 |
4. | 3.88e+07 2.42e+11 78.92401 |
5. | 2.11e+07 9.66e+10 67.74216 |
|--------------------------------|
6. | 2.58e+07 1.31e+11 71.26711 |
7. | 6.61e+07 5.37e+11 90.16096 |
8. | 1.85e+07 7.93e+10 65.54388 |
9. | 3.36e+07 1.95e+11 76.15117 |
10. | 2.02e+07 9.11e+10 67.07458 |
|--------------------------------|
11. | 1.60e+07 6.38e+10 63.20601 |
12. | 1.69e+08 2.19e+12 113.9737 |
13. | 1.52e+07 5.91e+10 62.40993 |
14. | 1.44e+07 5.48e+10 61.62791 |
15. | 3.48e+07 2.05e+11 76.80495 |
|--------------------------------|
16. | 1.40e+07 5.27e+10 61.22091 |
17. | 3.27e+07 1.87e+11 75.62407 |
18. | 5.10e+07 3.64e+11 84.49852 |
19. | 2.91e+07 1.57e+11 73.46428 |
20. | 2.21e+07 1.04e+11 68.53466 |
|--------------------------------|
21. | 4.69e+07 3.21e+11 82.76472 |
22. | 1.44e+08 1.73e+12 109.5217 |
+--------------------------------+
. sysuse auto, clear
(1978 automobile data)
. edit
. edit price weight
. preserve
. gen price2 = price + 15
. gen weight1 = weight / 5
. save auto1.dta
file auto1.dta saved
. restore
. sysuse auto, clear
(1978 automobile data)
. list price2
variable price2 not found
r(111);
. clear
. input
nothing to input
r(104);
. input x y
x y
1. 1 2
2. 3 4
3. 4 5
4. end
. save mydata, replace
(file mydata.dta not found)
file mydata.dta saved
. sysuse mydata.dta, clear
. input str10 name age
name age
1. Mike 22
2. Bruce 21
3. end
. sysuse auto, clear(1978 automobile data). order price weight length foreign make mpg headroom. sort privevariable prive not foundr(111);. list price +--------+ | price | |--------| 1. | 4,099 | 2. | 4,749 | 3. | 3,799 .
第六章 程序6.1 标准的程序文件格式6.2 创造自己的命令：与 STATA 互致问候6.3 暂元 Macros: local/global6.4 自带命令参数6.5 scalar 标量6.6 临时变量和临时数据文件:tempvar 和 tempfile
6.1 标准的程序文件格式
6.2 创造自己的命令：与 STATA 互致问候
6.3 暂元 Macros: local/global
6.4 自带命令参数
6.5 scalar 标量
6.6 临时变量和临时数据文件:tempvar 和 tempfile
输出数据集的观测数量、变量数量、数据集的标题和数据集的创建时间：
describe, short
输出数据集的观测数量、变量数量、数据集的标题和数据集的创建时间、各变量名称及其类型（字符、整数、小数）和标签:
describe
输出各变量的观测数量、平均值、标准差和最值：
输出各变量的各变量的观测数量、平均值、标准差、最值、偏度、峰度和各分位数：
sum, detail
方法如下（假设变量名称为var1）
summarize var1, detail / 这是对变量var1的详细描述，里面包含变量的分位数、最大最小值、均数方差标准差，偏度峰度等；正态分布的偏度 Skewness=0；峰度 Kurtosis=3。
Skewness/Kurtosis tests
命令：sktest var1 / 结果如下
上图也包含了对Skewness（偏度）和Kurtosis（峰度）的检验，需两者均大于检验水准（你可以根据实际情况定为0.05等）
横截面数据：一个时间点多个个体的变量数据
时间序列数据：某个经济体在不同时间点的变量取值数据
面板数据：多个经济体在不同时点的上的数据。其中分为短面板和长面板，短面板指的是T较小，N较大；长面板指的是T较大，N较小。采用xtset N T 的时候，会显示数据是否是balance的，以及长短。
stata中一些基本操作
文件的操作
设置路径（这里可以直接复制电脑上的路径名称）
cd"C:\Users"
use xyz.dta,clear
