SAS软件对数据集一些简单操作

SAS软件对数据集一些简单操作Libname AA 'd:\SAS';
Data AA.feng;
Input a b c;
cards;
3 4 56 64 43 34
累加
DATA A;
INPUT X Y @@;
S+X;
CARDS;
3 5 7 9 20 21
;
PROC PRINT;
RUN;
;
run;
DATA D1;
INFILE ‘C:FIT.TXT'
INPUT NUM $ 1-4 SEX $ 5 H 6-9 W 10-11;
RUN;
建立数据集求均值
data a;
input name$sex$math chinese@@;
cards;
张三男82 96 刘四女81 98 王五男90 92 黄六女92 92 ；
proc print data=a;
proc means data=a mean;
var math chinese;
run;
保留列
data b;
set a;
keep name math;
run;
丢弃列
data b;
set b;
drop name;
run;
条件选择
data c;
set a;
if math>90 and chinese>90; run;
把超过九十分改为90分data aa;
set a;
if chinese>90 then chinese=90; run;
筛选行
data aaa ;
set a(firstobs=2 obs=3);
run;
拆分男女
data a1 a2;
set a;
select(sex);
when('男')output a1;
when('女')output a2; otherwise put sex='wrong'; end;
drop sex;
run;
合并
data new;
set a1(in=male) a2(in=female); if male=1 then sex='';
if female=1 then sex='';
run;
纵向合并Set
横向合并merge
重命名rename 改标志label
排序语句
proc sort data=a out=b;
by sex;
run;
分类by class 先用sort排序
proc print data=b;
by sex;
run;
区间估计与假设检验单样本总体均值的假设检验
data sjcj;
input A B@@;
cards;
78 71 63 44 72 61 89 84 91 74
49 51 68 55 76 60 85 77 55 39
;
run;
proc ttest h0=70 alpha = 0.01 data=sjcj;
var A;
run;
配对两样本均值的假设检验
proc ttest data=sjcj;
paired A*B;
run;
独立两样本均值的假设检验
data zzcpsj;
input f g$@@;
cards;
28.3 1 27.6 2 30.1 1 22.2 2 29 1 31 2
37.6 1 33.8 2 32.1 1 20 2 28.8 1 30.2 2
36 1 31.7 2 37.2 1 26 2 38.5 1 32 2
34.4 1 31.2 2 28 1 30 1
;
run;
proc ttest data=zzcpsj;
class g;
var f;
run;
判断正态分布
Proc univariate data=a normal；
Var ss1；
Run；看shapiro-wilk
回归分析线性回归
多元
Proc reg data=a;
Var y x1-x6;
Model y=x1-x6;
Run;
逐步
Model y=x1-x6/selection=stepwise;
Run;
非线性
画散点图
data a;
set gupiao;
proc gplot data=a;
plot price*low=1 price*speed=2;
symbol1 v=star i=rl cv=orange ci=blue w=1; symbol2 v=star i=rq cv=orange ci=blue w=1; run;
data a;
set b;
x2x2=x2*x2;
x1x2=x1*x2;
proc reg data=a;
var y x1 x2 x2x2 x1x2;
model y=x1 x2 x2x2 x1x2;
print cli;
run;
方差分析
单因素方差分析
proc anova data=b;
class hangye;
model tousu=hangye; run;
proc glm data=b; class hangye;
model tousu=hangye; run;
双因素方差分析
不考虑交互作用
Proc glm data=my; Class a b;
Model y=a b;
Run;
考虑交互作用
Proc glm data=my; Class a b;
Model y=a b a*b; Run;。