SAS--chapter9描述统计（means freq）

描述统计 means  /  freq

libname clinic 'D:sas';
proc means data=clinic.admit;
run;               *num变量自动计算mean，sd，max，min;
proc means data=clinic.admit median range; *prco means data=  statistic;
run;
proc means data=clinic.admit min maxdec=2; *最大的小数点为2;
run;
proc means data=clinic.admit ;
    var age height;           *指定变量 or  item1-item6;
run;
proc means data=clinic.admit ;
    var age height;  
    class sex;  *根据sex将数据分组，可以多个变量。该变量值必须是有限个个数，cha和num都可以; 
run;


proc sort data=clinic.admit out=clinic.admitsort;
    by sex actlevel;         
run;
proc means data=clinic.admitsort ;
    var height weight;
    by sex actlevel;     *类似与class，但是需要提前sort;
run;

*输出;
proc means data=clinic.admit noprint;  *不打印上半部分;
    var age height;    
    class sex; 
        output out=work.data_gender    
        mean = aveage aveheight;      *输出 opt=libref.dataname mean=（输出均数），aveage=变量名;
run;
proc print data=work.data_gender;   *print刚刚的输出;
run;

proc freq data=clinic.admit2;  *数据集中每一个分类变量的频数，百分比，累计频数，累计百分比;
run;
proc freq data=clinic.admit2;  
    table paid  location;       *列出某些分类变量  or  table item1-item4;
run;
proc freq data=clinic.admit2 ;  
    table paid location /nocum;   *不显示累计频数和累计百分比;
run;

proc freq data=clinic.admit2 ; 
    tables paid*location;   *crosstable ，cells contain 频数，total freq，row f,column f;
run;                        *还可以是 a*b*c，a为level，b is row , c is column:

*combine format;
proc format;
    value wtfmt low-139='< 140'
                140-180='140-180'
                181-high='> 180';

    value htfmt low-64='< 5''5"'
                65-70='5''5-10"'
                71-high='> 5''10"';
run;
proc freq data=clinic.diabetes;
    tables weight*height;
    format weight wtfmt. height htfmt.;
run;

proc freq data=clinic.admit2 ; 
    tables paid*location / crosslist;  *check the different with no crosslist;
run;

proc freq data=clinic.admit2 ; 
    tables paid*location / list;    *more compact and clear
run;

proc freq data=clinic.admit2 ; 
    tables paid*location / nofreq norow nocol;   *suppress table;
run;

proc means data=clinic.heart min max maxdec=1;
   var arterial heart cardiac urinary;
   class survive sex;
run;


proc summary data=clinic.diabetes;
   var age height weight;
   class sex;
   output out=work.sum_gender
      mean=AvgAge AvgHeight AvgWeight;
run; 


proc freq data=clinic.heart order=freq;
   tables sex*survive*shock / nopercent list;
run;