Reputation: 307
Suppose the dataset has three columns
Date Region Price
01-03 A 1
01-03 A 2
01-03 B 3
01-03 B 4
01-03 A 5
01-04 B 4
01-04 B 6
01-04 B 7
I try to get the lead price by date and region through following code.
data want;
set have;
by _ric date_l_;
do until (eof);
set have(firstobs=2 keep=price rename=(price=lagprice)) end=eof;
end;
if last.date_l_ then call missing(lagprice);
run;
However, the WANT only have one observations. Then I create new_date=date
and try another code:
data want;
set have nobs=nobs;
do _i = _n_ to nobs until (new_date ne Date);
if eof1=0 then
set have (firstobs=2 keep=price rename=(price=leadprice)) end=eof1;
else leadprice=.;
end;
run;
With this code, SAS is working slowly. So I think this code is also not appropriate. Could anyone give some suggestions? Thanks
Upvotes: 1
Views: 2794
Reputation: 873
Try sorting by the variables you want lead price for then set together twice:
data test;
length Date Region $12 Price 8 ;
input Date $ Region $ Price ;
datalines;
01-03 A 1
01-03 A 2
01-03 B 3
01-03 B 4
01-03 A 5
01-04 B 4
01-04 B 6
01-04 B 7
;
run;
** sort by vars you want lead price for **;
proc sort data = test;
by DATE REGION;
run;
** set together twice -- once for lead price and once for all variables **;
data lead_price;
set test;
by DATE REGION;
set test (firstobs = 2 keep = PRICE rename = (PRICE = LEAD_PRICE))
test (obs = 1 drop = _ALL_);
if last.DATE or last.REGION then do;
LEAD_PRICE = .;
end;
run;
Upvotes: 2
Reputation: 12909
You can use proc expand
to generate leads on numeric variables by group. Try the following method instead:
Step 1: Sort by Region, Date
proc sort data=have;
by Region Date;
run;
Step 2: Create a new ID variable to denote observation numbers
Because you have multiple values per date per region, we need to generate a new ID variable so that proc expand
uses lead
by observation number rather than by date
.
data have2;
set have;
_ID_ = _N_;
run;
Step 3: Run proc expand
by region with the lead
transformation
lead
will do exactly as it sounds. You can lead by as many values as you'd like, as long as the data supports it. In this case, we are leading by one observation.
proc expand data=have2
out=want;
by Region;
id _ID_;
convert Price = Lead_Price / transform=(lead 1) ;
run;
Upvotes: 0