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data nasrlab.sales;
input id 1-4 name $ 5-8 date mmddyy10. sale 19-23 expense 24-28;
datalines;
001 abc 02012016 5000 2000
002 ahd 02042016 4000 1000
003 abc 03022016 6000 2500
004 ahd 02122016 4200 1100
;
run;
proc print data=nasrlab.sales;
format date mmddyy10. sale dollar. expense dollar.;
run;
data labedsales;
set nasrlab.sales;
label name="saleman"
sale="reveue"
;
run;
proc means data=nasrlab.sales;
var sale expense;
output out=maximas
max =maxsales maxexp
maxid (sale (name) expense(name))=effecient inefficient;
run;
_________________________
proc univariate data=sashelp.heart;
var Weight;
run;
proc univariate data=sashelp.heart;
var Weight;
qqplot/ normal(mu=est sigma=est color=green);
run;
proc univariate data=nasrlab.sales trimmed=0.1 0.01
winsorized=0.1
robustscale;
var sale;
run;
proc univariate data=height;
var hight weight;
pctlpre= w h
pctlpts= 12 15 89 45;
run;
___________________________
proc freq data=sashelp.heart;
table ageatdeath status;
run;
proc freq data=sashelp.heart;
table ageatdeath*status/missing;
run;
proc freq data=sashelp.heart;
table Smoking_Status*DeathCause/chisq;
run;
proc freq data=sashelp.heart;
by sex;
table Smoking_Status*DeathCause;
run;
proc freq data=nasrlab.grade;
table gender*section;
table gender*section/plot=freqplot(type=dot);
weight score;
run;
__________________________________________
proc corr data=nasrlab.sales proc corr data=nasrlab.sales;
run;
proc corr data=nasrlab.sales kendall pearson spearman fisher;
run;
proc corr data=nasrlab.sales alpha;
run;
proc corr data=nasrlab.sales csscp cov;
run;
proc corr data=nasrlab.sales plots=matrix(histogram);
run;
____________________________________________
PROC PRINT DATA=nasrlab.toy; RUN;
proc sort data=nasrlab.toy;
by country;
run;
proc transpose data=nasrlab.toy out=toytrans;
by country;
run;
data paneltoy (rename=(col1=ptl col2=pgrt col3=srfa));
set toytrans;
run;
proc panel data=toytrans;
id country _name_;
lag col1(1)/out=lagpanel;
run;
data lgdif;
set toytrans;
by country;
lgc1=lag(col1);
lgc2=lag (col2);
lgc3= lag(col3);
dfc1=dif (col1);
dfc2=dif (col2);
dfc3=dif(col3);
run;
____________________________________________
data baseball2;
set sashelp.baseball;
format Division DOLLAR8.;
label salary ='salary in 1000';
run;
data base1 (keep=name--yrmajor);
set sashelp.baseball;
run;
data base3;
set base2;
if name='Griffin, Alfredo' then natbat=.;
run;
data base2;
set base3;
obs+1;
run;
proc means data=base2;
run;
proc print data=base2;
where natbat=.;
run;
proc means data=base2 mean;
var natbat;
where nruns=74;
run;
proc means data=base2 mean;
where yrmajor=11 ;
where nbb=34;
var natbat;
run;
data base3;
set base2;
if name='Griffin, Alfredo' then natbat=510;
run;
proc means data=base3;
var nruns;
output out=maxee
max=runnnsss
min=rn
maxid(nruns(name))=maxrun
minid (nruns(name))=minrun;
run;
______________________________________
data dummy;
set sashelp.iris;
if species='Setosa' then dsetosa=1;
else dsetosa=0;
if species='Versicolor' then dver=1;
else dver=0;
run;
data asn;
set nasrlab.tours;
totcost=aircost+20;
run;
data asn;
set nasrlab.tours;
totcost=sum(aircost,20);
run;
data asn;
set nasrlab.tours;
if vendors='hispania' then nobonus = 'yes';
else if vendors='major' then bonus= 'yes';
else bonus='dontknw';
run;
data asn;
set nasrlab.tours;
if vendors='hispania' then bonus = 'null';
else if vendors='major' then bonus= 'allpeoples';
else bonus='for5plus';
run;
data asn;
set nasrlab.tours;
if vendors='hispania' then delete;
run;
data asn;
set nasrlab.tours;
mult=aircost*landcost;
add=aircost+landcost;
sub=aircost-landcost;
run;
data asn;
set nasrlab.tours;
nigtsr=round(nights,5);
landcr=round(landcost,50);
run;
data asn;
set nasrlab.tours;
totcostrnd=round(sum(aircost,landcost),5);
run;
data asn;
set nasrlab.tours;
totcostrnd=round(sum(aircost,landcost),5);
run;
data asn;
set nasrlab.airtour;
if tourguide=backupguide then remark='problem';
else if tourguide='' or backupguide ='' then remark='check';
else remark='ok';
run;
data asn;
set nasrlab.airtour;
part1=scan(eventdescription,2,',');
run;
data asn;
set nasrlab.airtour;
part1=scan(eventdescription,2,',');
part1left=left(scan(eventdescription,2,','));
partc1right=right(scan(eventdescription,2,','));
run;
data asn;
set nasrlab.airtour;
allguide=tourguide||backupguide;
run;
data asn;
set nasrlab.airtour;
allguide=trim(tourguide||backupguide);
run;
data asn;
set nasrlab.airtour;
allguide=tourguide||'/'||backupguide;
run;
data nn;
set abd;
if status='Dead' then remarks=deathcause||'
';
else remarks =('bp='|| Bp_Status||'wgtstus=' ||
Weight_Status||'smkgstatus='||Smoking_Status||'chlstatus='||
cholesterol_Status);
run;
data asn;
set nasrlab.airtour;
if landcost=. then tour ='pata nae';
else if landcost<500 then tour='sasta';
else if landcost<1000 then tour ='guzara';
else tour='mehnga';
run;
data sng;
set nasrlab.airtour;
if 500<=landcost<=1000 then type='medium';
else if 1000<landcost then type='high';
else type='low';
run;
data sng;
set nasrlab.airtour;
if (nights>3 or numberofevents>5) and (tourguide='Lucas' or city='Paris')
then type='mixture';
else type='olamba';
run;
data sng;
set nasrlab.airtour;
if landcost then rmarks='nonmissing';
run;
data sng;
set nasrlab.airtour;
if tourguide='lucas' then group='a';
else group='b';
run;
data sng;
set nasrlab.airtour;
if upcase(tourguide)='LUCAS' then group='a';
else group='b';
run;
data sng;
set nasrlab.airtour;
if tourguide= : 'L' then choosen='yes';
else choosen='no';
run;
data sng;
set nasrlab.airtour;
if index(eventdescription, 'other') then doubt='yes';
else doubt='no';
run;
data abc;
set nasrlab.airtour;
if index(eventdescription, 'other')then rewiev='yes';
else rewiev='no';
event=index(eventdescription, 'M');
eventm=substr(eventdescription,1,3);
run;
data sng;
set nasrlab.airtour;
if nights>=6;
run;
data sng abc;
set nasrlab.airtour;
if nights>=6 then output sng;
else output abc;
run;
data sng abc;
set nasrlab.airtour;
if tourguide='Lucas' then output sng;
else output abc;
ngghts=nights+1;
run;
proc print data=sng;
run;
data sng abc;
set nasrlab.airtour;
ngghts=nights+1;
if tourguide='Lucas' then output sng;
else output abc;
run;
data ab bc de fg;
set nasrlab.airtour;
if tourguide='Lucas' then output ab;
else output bc;
if nights > 6 then output de;
else output=fg;
run;
proc sort data=nasrlab.airtour out=abcd;
by city;
run;
data cars;
set sashelp.cars;
run;
proc sort data=cars;
by type;
run;
proc means data=cars;
by origin type;
run;
data crr;
set cars;
by type;
abc=first.Type;
def=last.Type;
run;
proc sort data=nasrlab.airtour out=nodps noduprecs;
by city;
data abc;
set nasrlab.data6 nasrlab.data7;
run;
data abc2;
set nasrlab.data6 nasrlab.data7;
by year;
run;
data abc3;
merge nasrlab.data6 nasrlab.data7;
run;
data abc4;
set nasrlab.data6;
if year=1997 then delete;
run;
data abc3;
merge abc4 nasrlab.data7;
run;
data abc3;
merge abc4 nasrlab.data7;
by year;
run;
data abc5;
merge nasrlab.class(drop= year major)
nasrlab.class2(drop=year major rename=(name=name2));
run;
data abc6;
merge nasrlab.class
nasrlab.class2(rename=(name=name2 year=year2 major=major2));
run;
data abc7;
merge nasrlab.company nasrlab.finance;
by name;
run;
proc sort data=nasrlab.shoes;
by type;
run;
proc sort data=nasrlab.discount;
by type;
run;
data nasrlab.shoes2;
set nasrlab.shoes2;
if type='C-Trian' then type='C-Train';
run;
data abc8;
merge nasrlab.shoes2 nasrlab.discount;
by type;
run;
data abc8;
merge nasrlab.shoes2 nasrlab.discount;
by type;
discountamont=regularprice*adjustment;
newprce=regularprice-discountamont;
run;
proc means data=abc8;
var newprce;
by type;
output out=summary sum(newprce)=total;
run;
data abc;
MERGE abc8 summary (drop= _TYPE_ _FREQ_);
by type;
run;
data abc8;
merge nasrlab.shoes2 nasrlab.discount;
by type;
discountamont=regularprice*adjustment;
newprce=regularprice-discountamont;
run;
proc means data=abc8;
var newprce;
by type;
output out=summary sum(newprce)=total;
run;
data abc;
MERGE abc8 summary (drop= _TYPE_ _FREQ_);
by type;
run;
data pca3(keep= item13--item26);
set nasrlab.pca3;
run;
proc factor data=pca3
simple
method=prin
priors=one
scree
rotate=varimax
round
flag=0.4;
var item13--item26;
run;
proc factor data=pca3 out=pcaresults (rename=(factor1=intrustchr
factor2=intrvw))
simple
method=prin
priors=one
nfactors=2
scree
rotate=varimax
round
flag=0.4;
var item13--item26;
data base12 (keep=name--yrmajor);
set sashelp.baseball;
run;
proc corr data=base12 PLOTS=matrix(histogram)plots(MAXPOINTS=none);
var natbat nhits nhome nrbi nbb;
run;
proc reg data=base12;
model nhits= nhome nrbi nbb yrmajor;
run;
proc reg data=base12;
model nhits= nhome nrbi nbb yrmajor;
output out=influe (keep=nhits nhome nrbi nbb yrmajor rsd lev ck dff)
rstudent=rsd h=lev cookd=ck dffits=dff;
run;
PROC PRINT DATA=INFLUE;
WHERE abs(rsd)>2;
RUN;
proc print data=influe;
where lev>(2*4+2)/322;
run;
proc print data=influe;
where abs(rsd)>2 AND lev>(2*4+2)/322;
run;
PROC PRINT DATA=INFLUE;
WHERE ck>4/322;
run;
proc print data=influe;
where dffit>2*srt(k)/n
data influe2;
set influe;
sn+1;
run;
proc reg data=influe2;
model nhits= nhome nrbi nbb yrmajor;
where sn NE 141;
run;
data basement;
set sashelp.baseball;
sn+1;
run;
proc reg data=basement;
model nhits= nhome nrbi nbb yrmajor/influence;
id sn;
run;
data base16;
set sashelp.baseball;
run;
data base17;
set base16;
if league='American' then dusa=1;
else dusa=0;
if league='National' then dnat=1;
else dnat=0;
run;
proc reg data=base17;
model nhits=dusa nhome nrbi nbb yrmajor;
run;
proc reg data=base17;
model nhits=dnat dusa nhome nrbi nbb yrmajor/noint;
run;
data base18;
set base17;
interusanbri=dusa*nRBI;
run;
proc reg data=base18;
model nhits=interusa nhome nrbi nbb yrmajor;
run;
proc reg data=abc;
model loginvice=MPG_CITY Weight dasia deurope;
output out=pred (keep=predctdinv)
predicted=predctdinv;
run;
proc reg data=abc;
model loginvice=MPG_CITY Weight dasia deurope/influence;
ods output outputstatistics=lps;
run;

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My All Codes of SAS

  • 1. data nasrlab.sales; input id 1-4 name $ 5-8 date mmddyy10. sale 19-23 expense 24-28; datalines; 001 abc 02012016 5000 2000 002 ahd 02042016 4000 1000 003 abc 03022016 6000 2500 004 ahd 02122016 4200 1100 ; run; proc print data=nasrlab.sales; format date mmddyy10. sale dollar. expense dollar.; run; data labedsales; set nasrlab.sales; label name="saleman" sale="reveue" ; run; proc means data=nasrlab.sales; var sale expense; output out=maximas max =maxsales maxexp maxid (sale (name) expense(name))=effecient inefficient; run; _________________________ proc univariate data=sashelp.heart; var Weight; run; proc univariate data=sashelp.heart; var Weight; qqplot/ normal(mu=est sigma=est color=green); run; proc univariate data=nasrlab.sales trimmed=0.1 0.01 winsorized=0.1 robustscale; var sale; run; proc univariate data=height; var hight weight; pctlpre= w h pctlpts= 12 15 89 45; run; ___________________________ proc freq data=sashelp.heart; table ageatdeath status; run; proc freq data=sashelp.heart; table ageatdeath*status/missing; run; proc freq data=sashelp.heart; table Smoking_Status*DeathCause/chisq; run; proc freq data=sashelp.heart; by sex; table Smoking_Status*DeathCause; run; proc freq data=nasrlab.grade; table gender*section; table gender*section/plot=freqplot(type=dot);
  • 2. weight score; run; __________________________________________ proc corr data=nasrlab.sales proc corr data=nasrlab.sales; run; proc corr data=nasrlab.sales kendall pearson spearman fisher; run; proc corr data=nasrlab.sales alpha; run; proc corr data=nasrlab.sales csscp cov; run; proc corr data=nasrlab.sales plots=matrix(histogram); run; ____________________________________________ PROC PRINT DATA=nasrlab.toy; RUN; proc sort data=nasrlab.toy; by country; run; proc transpose data=nasrlab.toy out=toytrans; by country; run; data paneltoy (rename=(col1=ptl col2=pgrt col3=srfa)); set toytrans; run; proc panel data=toytrans; id country _name_; lag col1(1)/out=lagpanel; run; data lgdif; set toytrans; by country; lgc1=lag(col1); lgc2=lag (col2); lgc3= lag(col3); dfc1=dif (col1); dfc2=dif (col2); dfc3=dif(col3); run; ____________________________________________ data baseball2; set sashelp.baseball; format Division DOLLAR8.; label salary ='salary in 1000'; run; data base1 (keep=name--yrmajor); set sashelp.baseball; run; data base3; set base2; if name='Griffin, Alfredo' then natbat=.; run; data base2; set base3; obs+1; run; proc means data=base2; run; proc print data=base2; where natbat=.; run; proc means data=base2 mean; var natbat; where nruns=74; run;
  • 3. proc means data=base2 mean; where yrmajor=11 ; where nbb=34; var natbat; run; data base3; set base2; if name='Griffin, Alfredo' then natbat=510; run; proc means data=base3; var nruns; output out=maxee max=runnnsss min=rn maxid(nruns(name))=maxrun minid (nruns(name))=minrun; run; ______________________________________ data dummy; set sashelp.iris; if species='Setosa' then dsetosa=1; else dsetosa=0; if species='Versicolor' then dver=1; else dver=0; run; data asn; set nasrlab.tours; totcost=aircost+20; run; data asn; set nasrlab.tours; totcost=sum(aircost,20); run; data asn; set nasrlab.tours; if vendors='hispania' then nobonus = 'yes'; else if vendors='major' then bonus= 'yes'; else bonus='dontknw'; run; data asn; set nasrlab.tours; if vendors='hispania' then bonus = 'null'; else if vendors='major' then bonus= 'allpeoples'; else bonus='for5plus'; run; data asn; set nasrlab.tours; if vendors='hispania' then delete; run; data asn; set nasrlab.tours; mult=aircost*landcost; add=aircost+landcost; sub=aircost-landcost; run; data asn; set nasrlab.tours; nigtsr=round(nights,5); landcr=round(landcost,50); run; data asn; set nasrlab.tours; totcostrnd=round(sum(aircost,landcost),5);
  • 4. run; data asn; set nasrlab.tours; totcostrnd=round(sum(aircost,landcost),5); run; data asn; set nasrlab.airtour; if tourguide=backupguide then remark='problem'; else if tourguide='' or backupguide ='' then remark='check'; else remark='ok'; run; data asn; set nasrlab.airtour; part1=scan(eventdescription,2,','); run; data asn; set nasrlab.airtour; part1=scan(eventdescription,2,','); part1left=left(scan(eventdescription,2,',')); partc1right=right(scan(eventdescription,2,',')); run; data asn; set nasrlab.airtour; allguide=tourguide||backupguide; run; data asn; set nasrlab.airtour; allguide=trim(tourguide||backupguide); run; data asn; set nasrlab.airtour; allguide=tourguide||'/'||backupguide; run; data nn; set abd; if status='Dead' then remarks=deathcause||' '; else remarks =('bp='|| Bp_Status||'wgtstus=' || Weight_Status||'smkgstatus='||Smoking_Status||'chlstatus='|| cholesterol_Status); run; data asn; set nasrlab.airtour; if landcost=. then tour ='pata nae'; else if landcost<500 then tour='sasta'; else if landcost<1000 then tour ='guzara'; else tour='mehnga'; run; data sng; set nasrlab.airtour; if 500<=landcost<=1000 then type='medium'; else if 1000<landcost then type='high'; else type='low'; run; data sng; set nasrlab.airtour; if (nights>3 or numberofevents>5) and (tourguide='Lucas' or city='Paris') then type='mixture'; else type='olamba'; run; data sng; set nasrlab.airtour; if landcost then rmarks='nonmissing'; run;
  • 5. data sng; set nasrlab.airtour; if tourguide='lucas' then group='a'; else group='b'; run; data sng; set nasrlab.airtour; if upcase(tourguide)='LUCAS' then group='a'; else group='b'; run; data sng; set nasrlab.airtour; if tourguide= : 'L' then choosen='yes'; else choosen='no'; run; data sng; set nasrlab.airtour; if index(eventdescription, 'other') then doubt='yes'; else doubt='no'; run; data abc; set nasrlab.airtour; if index(eventdescription, 'other')then rewiev='yes'; else rewiev='no'; event=index(eventdescription, 'M'); eventm=substr(eventdescription,1,3); run; data sng; set nasrlab.airtour; if nights>=6; run; data sng abc; set nasrlab.airtour; if nights>=6 then output sng; else output abc; run; data sng abc; set nasrlab.airtour; if tourguide='Lucas' then output sng; else output abc; ngghts=nights+1; run; proc print data=sng; run; data sng abc; set nasrlab.airtour; ngghts=nights+1; if tourguide='Lucas' then output sng; else output abc; run; data ab bc de fg; set nasrlab.airtour; if tourguide='Lucas' then output ab; else output bc; if nights > 6 then output de; else output=fg; run; proc sort data=nasrlab.airtour out=abcd; by city; run; data cars; set sashelp.cars; run; proc sort data=cars;
  • 6. by type; run; proc means data=cars; by origin type; run; data crr; set cars; by type; abc=first.Type; def=last.Type; run; proc sort data=nasrlab.airtour out=nodps noduprecs; by city; data abc; set nasrlab.data6 nasrlab.data7; run; data abc2; set nasrlab.data6 nasrlab.data7; by year; run; data abc3; merge nasrlab.data6 nasrlab.data7; run; data abc4; set nasrlab.data6; if year=1997 then delete; run; data abc3; merge abc4 nasrlab.data7; run; data abc3; merge abc4 nasrlab.data7; by year; run; data abc5; merge nasrlab.class(drop= year major) nasrlab.class2(drop=year major rename=(name=name2)); run; data abc6; merge nasrlab.class nasrlab.class2(rename=(name=name2 year=year2 major=major2)); run; data abc7; merge nasrlab.company nasrlab.finance; by name; run; proc sort data=nasrlab.shoes; by type; run; proc sort data=nasrlab.discount; by type; run; data nasrlab.shoes2; set nasrlab.shoes2; if type='C-Trian' then type='C-Train'; run; data abc8; merge nasrlab.shoes2 nasrlab.discount; by type; run; data abc8; merge nasrlab.shoes2 nasrlab.discount; by type;
  • 7. discountamont=regularprice*adjustment; newprce=regularprice-discountamont; run; proc means data=abc8; var newprce; by type; output out=summary sum(newprce)=total; run; data abc; MERGE abc8 summary (drop= _TYPE_ _FREQ_); by type; run; data abc8; merge nasrlab.shoes2 nasrlab.discount; by type; discountamont=regularprice*adjustment; newprce=regularprice-discountamont; run; proc means data=abc8; var newprce; by type; output out=summary sum(newprce)=total; run; data abc; MERGE abc8 summary (drop= _TYPE_ _FREQ_); by type; run; data pca3(keep= item13--item26); set nasrlab.pca3; run; proc factor data=pca3 simple method=prin priors=one scree rotate=varimax round flag=0.4; var item13--item26; run; proc factor data=pca3 out=pcaresults (rename=(factor1=intrustchr factor2=intrvw)) simple method=prin priors=one nfactors=2 scree rotate=varimax round flag=0.4; var item13--item26; data base12 (keep=name--yrmajor); set sashelp.baseball; run; proc corr data=base12 PLOTS=matrix(histogram)plots(MAXPOINTS=none); var natbat nhits nhome nrbi nbb; run; proc reg data=base12; model nhits= nhome nrbi nbb yrmajor; run; proc reg data=base12; model nhits= nhome nrbi nbb yrmajor; output out=influe (keep=nhits nhome nrbi nbb yrmajor rsd lev ck dff)
  • 8. rstudent=rsd h=lev cookd=ck dffits=dff; run; PROC PRINT DATA=INFLUE; WHERE abs(rsd)>2; RUN; proc print data=influe; where lev>(2*4+2)/322; run; proc print data=influe; where abs(rsd)>2 AND lev>(2*4+2)/322; run; PROC PRINT DATA=INFLUE; WHERE ck>4/322; run; proc print data=influe; where dffit>2*srt(k)/n data influe2; set influe; sn+1; run; proc reg data=influe2; model nhits= nhome nrbi nbb yrmajor; where sn NE 141; run; data basement; set sashelp.baseball; sn+1; run; proc reg data=basement; model nhits= nhome nrbi nbb yrmajor/influence; id sn; run; data base16; set sashelp.baseball; run; data base17; set base16; if league='American' then dusa=1; else dusa=0; if league='National' then dnat=1; else dnat=0; run; proc reg data=base17; model nhits=dusa nhome nrbi nbb yrmajor; run; proc reg data=base17; model nhits=dnat dusa nhome nrbi nbb yrmajor/noint; run; data base18; set base17; interusanbri=dusa*nRBI; run; proc reg data=base18; model nhits=interusa nhome nrbi nbb yrmajor; run; proc reg data=abc; model loginvice=MPG_CITY Weight dasia deurope; output out=pred (keep=predctdinv) predicted=predctdinv; run; proc reg data=abc; model loginvice=MPG_CITY Weight dasia deurope/influence; ods output outputstatistics=lps; run;