Recently in the SAS Community Library: Your often contains the information you need, but not sequenced in the order required for processing. @SASJedi shows you how to properly sequence data so you can compare the data in one table to the data in another, conduct merges or joins and more.
Thanks to a little math help from StackExchange, here's a SAS ODS Graphics Happy Father's Day greeting!
* Fun w/SAS ODS Graphics: Happy Father's Day! (Scatter + Polygon + Text Plots)
Star vertices algorithm from math.stackexchange.com/questions/3582342/coordinates-of-the-vertices-of-a-five-pointed-star;
data star; * Generate points for stars;
retain id 0 r1 6 r2 2.5 dad "DAD" xT 0 yT 0; * Star outer radius is 6, inner radius is 2.5;
pi=constant("pi");
do pt=1 to 600; * Points for 600 little Unicode stars;
xS=-6.25+12.5*ranuni(123); yS=-5.75+12.5*ranuni(456); output;
end;
xS=.; yS=.;
do k=0 to 4; * Points for 1 big polygon star;
x=r1*cos(2*pi*k/5+pi/2); y=r1*sin(2*pi*k/5+pi/2); output;
x=r2*cos(2*pi*k/5+pi/2+2*pi/10); y=r2*sin(2*pi*k/5+pi/2+2*pi/10); output;
end;
ods graphics / reset width=5in height=5in noborder; * Make Dad a star!;
proc sgplot noautolegend aspect=1 noborder nowall pad=0;
styleattrs backcolor=navy;
symbolchar name=uniStar char='2605'x; * Unicode value for 5-pointed star;
scatter x=xS y=yS / markerattrs=(symbol=unistar color=White size=24pt); * Plot little unicode stars;
polygon x=x y=y id=id / fill fillattrs=(color=cxd9d9d9) dataskin=crisp; * Plot big polygon star;
text x=xT y=yT text=dad / contributeoffsets=none textattrs=(size=48pt color=navy weight=bold) contributeoffsets=none; * "DAD";
xaxis display=none values=(-6.25 6.25) offsetmin=.01 offsetmax=.01; * Hide axes;
yaxis display=none values=(-5.75 6.75) offsetmin=.01 offsetmax=.01;
run;
... View more
Boa tarde, tenho duas tabelas e gostaria de gerar/exportar um arquivo único, em que, cada tabela ficasse em uma aba do excel. Como fazer este procedimento?
... View more
Hey SAS Community, I am new to SAS and would appreciate any advice on this topic. For a university project, I need to calculate the expected sales value for the upcoming months after my dataset runs out. The dataset includes Total_amt , which contains the transaction values, and Tran_date , which specifies the dates of the transactions. data TransactionsWithSasDate;
set Transactions;
Tran_date = mdy(Month, Day, Year);
format Tran_date date9.;
run;
proc sql;
create table MonthlySales as
select
intnx('Month', Tran_date, 0, 'Beginning') as Month format=date9.,
sum(Total_amt) as MonthlySalesValue
from TransactionsWithSasDate
group by calculated Month;
quit;
proc arima data=MonthlySales;
identify var=MonthlySalesValue(12);
estimate p=1 q=1;
forecast lead=12 id=Month interval=Month out=ForecastedSalesValue;
run;
proc sgplot data=ForecastedSalesValue;
series x=Month y=MonthlySalesValue / lineattrs=(color=blue) legendlabel="Actual";
series x=Month y=Forecast / lineattrs=(color=red) legendlabel="Forecast";
xaxis label='Month';
yaxis label='Monthly sales value';
title 'Monthly Sales Trend and Forecast';
run; I double-checked my code, but I am not sure if it is correct because the output graph looks a little off. Any advice on this topic would be highly appreciated! Greetings, Johannes
... View more
Hi everyone, data tab1;
input gr $ experiment var1;
datalines;
A 1 0.58
A 2 0.74
A 3 1.17
B 1 0.73
B 2 0.75
B 3 1.52
C 1 1.09
C 2 1.06
C 3 1.60
;
run;
proc npar1way data=tab1 wilcoxon dscf;
class gr;
var var1;
run; I have 3 subjects (A, B and C). For each subject, i repeat an experient 3 times. So I have 3 quantitave measurements for each subject. Looking at the data, I realize that in each experiment (1, 2 and 3), A < B < C. But for each experiment I don't have the same "order of magnitude" for my quantitative variable, because of manipulation errors. I wanted to do a kruskall-wallis because of the small sample, to test my quantitative variable between my 3 groups. But I don't know how to take into account the fact that there is inter-experimental variability because one and only one CLASS variable must be specified ? And is the kruslll-wallis test the best solution ? Thank you.
... View more
I'm trying to use MIANALYZE on the ODS output dataset called ROCASSOCIATION that comes out of the logistic procedure. I'm trying to combine multiple AUCs. Help please!
ods output ROCAssociation=ROCAssociation;
proc logistic data=both plots=roc(id=prob);
by _imputation_;
model y(event='Yes') = x / nofit ;
roc 'X' x;
run; Then... PROC MIANALYZE ??????
... View more