教程

5.加权excel示例.png

  1. if(age<=19)          Age_cnnic=1 .
  2. if(age>=20 & age<=29)Age_cnnic=2 .
  3. if(age>=30 & age<=39)Age_cnnic=3 .
  4. if(age>=40 & age<=49)Age_cnnic=4 .
  5. if(age>=50)          Age_cnnic=5.
  6. exe.
  7. VARIABLE LABELS Age_cnnic '[Age_cnnic]年龄段'.
  8. Value Labels Age_cnnic
  9. 1    '<20'
  10. 2    '20-29'
  11. 3    '30-39'
  12. 4    '40-49'
  13. 5    '>49'
  14. .
  16. * 配比前数据结果.
  17. WEIGHT OFF.
  18. CTABLES
  19.   /VLABELS VARIABLES=Z1 Age_cnnic DISPLAY=LABEL
  20.   /TABLE Z1[C]>Age_cnnic[C][COUNT F40.0, LAYERPCT.COUNT PCT40.1]
  21.   /CATEGORIES VARIABLES=Z1 Age_cnnic ORDER=A KEY=VALUE EMPTY=INCLUDE.
  23. *配比赋值.
  24. if(Z1=1 & Age_cnnic=1)peibi1=0.449588422980849.                
  25. if(Z1=1 & Age_cnnic=2)peibi1=0.630263278899083.                
  26. if(Z1=1 & Age_cnnic=3)peibi1=1.32837908333333.                
  27. if(Z1=1 & Age_cnnic=4)peibi1=1.5039717309417.                
  28. if(Z1=1 & Age_cnnic=5)peibi1=1.19639244660194.                
  29. if(Z1=2 & Age_cnnic=1)peibi1=0.72293889010989.                
  30. if(Z1=2 & Age_cnnic=2)peibi1=1.69798698522167.                
  31. if(Z1=2 & Age_cnnic=3)peibi1=3.27135726530612.                
  32. if(Z1=2 & Age_cnnic=4)peibi1=4.06476428169014.                
  33. if(Z1=2 & Age_cnnic=5)peibi1=4.24250038095238.                
  36. exe.
  37. VARIABLE LABELS peibi1 '【配比1】cnnic'.
  39. *样本配比加权.
  40. WEIGHT BY peibi1.
  41. exe.
  43. *配比后结果对比.
  44. CTABLES
  45.   /VLABELS VARIABLES=Z1 Age_cnnic DISPLAY=LABEL
  46.   /TABLE Z1[C]>Age_cnnic[C][COUNT F40.0, LAYERPCT.COUNT PCT40.1]
  47.   /CATEGORIES VARIABLES=Z1 Age_cnnic ORDER=A KEY=VALUE EMPTY=INCLUDE.

数据转换、频次、平均数

  1. *数据转换，变量不变.
  2. RECODE str_user_sex ('女'='0') ('男'='1').
  3. EXECUTE.
  4. RECODE str_user_age ('0-18'='1') ('18-25'='2') ('25-30'='3') ('30-40'='4') ('40-50'='5') ('50-60'='6') ('60+'='7').
  5. EXECUTE.
  6. RECODE str_user_city ('一线城市'='1') ('二线城市'='2') ('三线城市'='3') ('四线城市'='4') ('五线城市'='5') ('未知'='0').
  7. EXECUTE.
  8. RECODE str_login_time ('近1周'='1') ('近1个月'='2') ('近3个月'='3') ('近6个月'='4') ('近1年'='5') ('1年以上'='6').
  9. EXECUTE.
  10. RECODE str_login_count ('1-3次'='1') ('4-10次'='2') ('11-50次'='3') ('超过50次'='4').
  11. EXECUTE.
  13. *芝麻分等级编码，编码为不同变量.
  14. RECODE credit_score (Lowest thru 549=1) (550 thru 599=2) (600 thru 649=3) (650 thru 699=4) (700 thru 749=5) (750 thru Highest=6) INTO 芝麻分等级.
  15. EXECUTE.
  17. *频次统计.
  18. FREQUENCIES VARIABLES=str_user_sex str_user_age str_user_city str_login_time str_login_count
  19.   /HISTOGRAM NORMAL
  20.   /ORDER=ANALYSIS.
  22. FREQUENCIES VARIABLES=芝麻分等级
  23.   /ORDER=ANALYSIS.
  25. *平均数.
  26. FREQUENCIES VARIABLES=芝麻分等级
  27.   /ORDER=ANALYSIS.