So I have this code which aims to left join a new interest rate based on its original maturity. for example, if the original maturity is 0.25 years, I want it to append on the interest rate for a 3 month rate.
The code looks like
data want;
set maturity;
retain tempMat tempRate;
i = 1;
do until(stop eq 1);
set Maturity2 nobs = num point = i;
diff = abs(sum(Maturity, -OriginalMaturity));
if i eq 1 then
do;
tempMat = diff;
tempRate = Base_Rate_New;
end;
else
do;
if i = num then
do;
stop = 1;
Rate_ok = Base_Rate_New;
end;
else if diff gt tempMat then
do;
stop = 1;
Rate_ok = tempRate;
end;
else
do;
tempMat = diff;
tempRate = Base_Rate_New;
end;
end;
i = i + 1;
end;
end;
run;
The two tables look like
data maturity;
input ID maturity base_rate;
datalines
1 0.25 1
2 0.5 1
3 0.6 2
4 0.3 3
5 1.2 1.2
6 1.5 2
7 2 3
8 3 1
9 1 0.5
;
data maturity2;
input originalmaturity base_rate_new;
datalines
0.25 2
0.5 3
0.75 1
1 3
;
run;
the dataset that I look to create would look like (after dropping all the extra variables
data want;
input ID maturity base_rate base_rate_new;
datalines
1 0.25 1 2
2 0.5 1 3
3 0.6 2 3
4 0.3 3 2
5 1.2 1.2 3
6 1.5 2 3
7 2 3 3
8 3 1 3
9 1 0.5 3
;
run;
The problem is that currently if the value exceeds the closer number, it still chooses the higher number. For example if it is 0.3 it would choose the 0.5 instead of 0.25
data want;
set maturity;
retain tempDiff Rate;
do point=1 to n;
set maturity2 nobs=n point=point;
diff=abs(maturity-originalmaturity);
if point=1 then do;
tempDiff=diff;
Rate=base_rate_new;
end;
else if diff<tempDiff then do;
tempDiff=diff;
Rate=base_rate_new;
end;
end;
drop diff tempDiff originalmaturity base_rate_new;
run;
Assuming the second data set is sorted in ascending order, then you need to find the 2 rates that surround the value and check which is closer. You have to handle the edge case where you have an exact match or when you get to the end of the second data set.
/*This assumes maturity2 is sorted ascending by originalmaturity*/
data want(keep=ID maturity originalmaturity base_rate base_rate_new);
set maturity;
stop = 0;
i = 1;
do until(stop eq 1);
set Maturity2 nobs = num point = i;
/* put _all_;*/
if originalmaturity = maturity then do;
output;
stop = 1;
end;
else if originalmaturity < maturity then do;
ldist = abs(originalmaturity - maturity);
lbrn = base_rate_new;
end;
else if originalmaturity > maturity then do;
hdist = abs(originalmaturity - maturity);
if hdist > ldist then
base_rate_new = lbrn;
output;
stop = 1;
end;
if num = i then do;
output;
stop = 1;
end;
i = i + 1;
end;
run;
Related
Every Subject has a baseline. Once the difference between the value and the baseline exceeds 5, that value becomes the baseline for all future comparisons until another value exceeds this new baseline by 5.
This is what I want the output data to look like:
This is what I'm getting
This is my current code, which gets me as close as anything I've tried. I've tried different combinations of retain, lag(), and ifn (suggested in this post)
Data Have;
Input Visit usubjid Baseline Value;
datalines;
1 1 112.2 112.2
2 1 112.2 113.7
3 1 112.2 112
3 1 112.2 108
4 1 112.2 109
5 1 112.2 107
7 1 112.2 106
8 1 112.2 107
;
run;
proc sort;by usubjid;run;
data want;
Length chg $71;
retain chg;
set Have;
length prevchg $71;
by usubjid;
prevchg=chg;
if first.usubjid then do; prevchg=''; end;
baseline=ifn(prevchg in ('Increase >= 5mm New', "Decrease >= 5mm"),lag(value),lag(baseline));
diff = value-baseline;
if visit > 1 then do;
if diff > 5 then do; chg='Increase >= 5mm New'; order = 3; end;
else if diff < -5 then do; chg = 'Decrease >= 5mm'; order = 6; end;
else if -5 <= diff <= 5 then do;
if prevchg in('Increase >= 5mm New', 'Increase > 5mm Persistent') then do; chg ='Increase > 5mm Persistent'; order = 4; end;
else do; chg = 'No Change (change >= -5 and <= 5mm)'; order = 5; end;
end;
end;
run;
Right now the code will correctly update the baseline to the previous value for the next visit, but then goes right back to the original baseline. I'm confident this has something to do with the way Lag() and Retain work with if/then, but I cannot figure out the solution. here is an example of the issue:
You should be able to do this easily. The BASELINE variable CANNOT be on the input if you want to RETAIN its value.
data want ;
set have ;
by usubjid;
retain baseline;
if first.usubjid then baseline=value;
difference = baseline - value;
output;
if difference > 5 then baseline=value;
run;
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I have a large dataset containting over 80 000 000 rows sorted by "name" and "income" (with duplicates both for name and income). For the first name I would like to have the 5 lowest incomes. For the second name I would like to have the 5 lowest incomes (but incomes drawn to the first name are then disqualified to be selected). And so on, until the last name (if there are any incomes left at that time).
You first want to rank income within names. So:
proc rank data=yourdata out=temp ties=low;
by name;
var income;
ranks incomerank;
run;
Then you want to filter the 5 lowest incomes by name, so:
proc sql;
create table want as
select distinct *
from temp
where incomerank < 6;
quit;
You will need to sort and track incomes
Use an array to sort and track the lowest five income of a name.
Use a hash to track and check the observance of an income being output and thus ineligible for output by later names.
Example:
An insert sort of eligible low valued incomes is used and will be fast due to only 5 items.
data have;
call streaminit(1234);
do name = 1 to 1e6;
do seq = 1 to rand('integer', 20);
income = rand('integer', 20000, 1000000);
output;
end;
end;
run;
data
want (label='Lowest 5 incomes (first occurring over all names) of each name')
want_barren(keep=name label='Names whose all incomes were previously output for earlier names')
;
array X(5) _temporary_;
if _n_ = 1 then do;
if 0 then set have;
declare hash incomes();
incomes.defineKey('income');
incomes.defineDone();
end;
_maxmin5 = 1e15;
x(1) = 1e15;
x(2) = 1e15;
x(3) = 1e15;
x(4) = 1e15;
x(5) = 1e15;
do _n_ = 1 by 1 until (last.name);
set have;
by name;
if incomes.check() = 0 then continue;
* insert sort - lowest five not observed previously;
if income > _maxmin5 then continue;
do _i_ = 1 to 5;
if income < x(_i_) then do;
do _j_ = 5 to _i_+1 by -1;
x(_j_) = x(_j_-1);
end;
x(_i_) = income;
_maxmin5 = x(5);
incomes.add();
leave;
end;
end;
end;
_outflag = 0;
do _n_ = 1 to _n_;
set have;
if income in x then do;
_outflag = 1;
OUTPUT want;
end;
end;
if not _outflag then
OUTPUT want_barren;
drop _:;
run;
data have;
do n = 1 to 8e5;
do _N_ = 1 to 100;
income = ceil(rand('uniform') * 1e4);
address = cats('Address_', _N_);
output;
end;
end;
run;
data want(drop=c);
if _N_ = 1 then do;
dcl hash h(dataset : 'have(obs=0)', ordered : 'a', multidata : 'y');
h.definekey('income');
h.definedata(all : 'y');
h.definedone();
dcl hiter i('h');
dcl hash inc();
inc.definekey('income');
inc.definedone();
end;
do until (last.n);
set have;
by n;
h.add();
end;
do c = 0 by 0 while (i.next() = 0);
if inc.add() = 0 then do;
c + 1;
output;
end;
if c = 5 then leave;
end;
_N_ = i.first();
_N_ = i.prev();
h.clear();
run;
Here is my interpretation of your problem and a solution.
Suppose a simplified version of your data looks like this and you want the 2 lowest income for each name. For simplicity, I use a numeric variable n as name, but a character var will work as well.
data have;
input n income;
datalines;
1 100
1 200
1 300
2 400
2 100
2 500
3 600
3 200
3 500
;
From this data, my guess is that your logic goes like this:
Start with n = 1.
Output the 2 observations with the lowest income (100 and 200)
Go to the next name (n=2).
Output the 2 observations with the lowest income, that has not already been output (300 and 400). 200 Has been output in the n=1 group.
...And so on...
This gives the desired result below:
data want;
input n income;
datalines;
1 100
1 200
2 300
2 400
3 500
;
Try out the solution below and verify that you get the result as posted above.
data want(drop=c);
if _N_ = 1 then do;
dcl hash h(ordered : 'a', multidata : 'y');
h.definekey('income');
h.definedone();
dcl hiter i('h');
dcl hash inc();
inc.definekey('income');
inc.definedone();
end;
do until (last.n);
set have;
by n;
h.add();
end;
do c = 0 by 0 while (i.next() = 0);
if inc.add() = 0 then do;
c + 1;
output;
end;
if c = 2 then leave;
end;
_N_ = i.first();
_N_ = i.prev();
h.clear();
run;
Finally, let us create representable example data with 80Mio obs. I change the if c = 2 then leave; statement to if c = 5 then leave; to go back to your actual problem.
The code below runs in about 45 sec on my system and processes the data in a single pass. Let me know is it works for you :-)
data have;
do n = 1 to 8e5;
do _N_ = 1 to 100;
income = ceil(rand('uniform') * 1e4);
output;
end;
end;
run;
data want(drop=c);
if _N_ = 1 then do;
dcl hash h(ordered : 'a', multidata : 'y');
h.definekey('income');
h.definedone();
dcl hiter i('h');
dcl hash inc();
inc.definekey('income');
inc.definedone();
end;
do until (last.n);
set have;
by n;
h.add();
end;
do c = 0 by 0 while (i.next() = 0);
if inc.add() = 0 then do;
c + 1;
output;
end;
if c = 5 then leave;
end;
_N_ = i.first();
_N_ = i.prev();
h.clear();
run;
I have a dataset that looks like:
Hour Flag
1 1
2 1
3 .
4 1
5 1
6 .
7 1
8 1
9 1
10 .
11 1
12 1
13 1
14 1
I want to have an output dataset like:
Total_Hours Count
2 2
3 1
4 1
As you can see, I want to count the number of hours included in each period with consecutive "1s". A missing value ends the consecutive sequence.
How should I go about doing this? Thanks!
You'll need to do this in two steps. First step is making sure the data is sorted properly and determining the number of hours in a consecutive period:
PROC SORT DATA = <your dataset>;
BY hour;
RUN;
DATA work.consecutive_hours;
SET <your dataset> END = lastrec;
RETAIN
total_hours 0
;
IF flag = 1 THEN total_hours = total_hours + 1;
ELSE
DO;
IF total_hours > 0 THEN output;
total_hours = 0;
END;
/* Need to output last record */
IF lastrec AND total_hours > 0 THEN output;
KEEP
total_hours
;
RUN;
Now a simple SQL statement:
PROC SQL;
CREATE TABLE work.hour_summary AS
SELECT
total_hours
,COUNT(*) AS count
FROM
work.consecutive_hours
GROUP BY
total_hours
;
QUIT;
You will have to do two things:
compute the run lengths
compute the frequency of the run lengths
For the case of using the implict loop
Each run length occurnece can be computed and maintained in a retained tracking variable, testing for a missing value or end of data for output and a non missing value for run length reset or increment.
Proc FREQ
An alternative is to use an explicit loop and a hash for frequency counts.
Example:
data have; input
Hour Flag; datalines;
1 1
2 1
3 .
4 1
5 1
6 .
7 1
8 1
9 1
10 .
11 1
12 1
13 1
14 1
;
data _null_;
declare hash counts(ordered:'a');
counts.defineKey('length');
counts.defineData('length', 'count');
counts.defineDone();
do until (end);
set have end=end;
if not missing(flag) then
length + 1;
if missing(flag) or end then do;
if length > 0 then do;
if counts.find() eq 0
then count+1;
else count=1;
counts.replace();
length = 0;
end;
end;
end;
counts.output(dataset:'want');
run;
An alternative
data _null_;
if _N_ = 1 then do;
dcl hash h(ordered : "a");
h.definekey("Total_Hours");
h.definedata("Total_Hours", "Count");
h.definedone();
end;
do Total_Hours = 1 by 1 until (last.Flag);
set have end=lr;
by Flag notsorted;
end;
Count = 1;
if Flag then do;
if h.find() = 0 then Count+1;
h.replace();
end;
if lr then h.output(dataset : "want");
run;
Several weeks ago, #Richard taught me how to use DOW-loop and direct addressing array. Today, I give it to you.
data want(keep=Total_Hours Count);
array bin[99]_temporary_;
do until(eof1);
set have end=eof1;
if Flag then count + 1;
if ^Flag or eof1 then do;
bin[count] + 1;
count = .;
end;
end;
do i = 1 to dim(bin);
Total_Hours = i;
Count = bin[i];
if Count then output;
end;
run;
And Thanks Richard again, he also suggested me this article.
I checked out this previous post (LINK) for potential solution, but still not working. I want to sum across rows using the ID as the common identifier. The num variable is constant. The id and comp the two variables I want to use to creat a pct variable, which = sum of [comp = 1] / num
Have:
id Comp Num
1 1 2
2 0 3
3 1 1
2 1 3
1 1 2
2 1 3
Want:
id tot pct
1 2 100
2 3 0.666666667
3 1 100
Currently have:
proc sort data=have;
by id;
run;
data want;
retain tot 0;
set have;
by id;
if first.id then do;
tot = 0;
end;
if comp in (1) then tot + 1;
else tot + 0;
if last.id;
pct = tot / num;
keep id tot pct;
output;
run;
I use SQL for things like this. You can do it in a Data Step, but the SQL is more compact.
data have;
input id Comp Num;
datalines;
1 1 2
2 0 3
3 1 1
2 1 3
1 1 2
2 1 3
;
run;
proc sql noprint;
create table want as
select id,
sum(comp) as tot,
sum(comp)/count(id) as pct
from have
group by id;
quit;
Hi there is a much more elegant solution to your problem :)
proc sort data = have;
by id;
run;
data want;
do _n_ = 1 by 1 until (last.id);
set have ;
by id ;
tot = sum (tot, comp) ;
end ;
pct = tot / num ;
run;
I hope it is clear. I use sql too because I am new and the DOW loop is rather complicated but in your case its pretty straightforward.
I have a dataset with 4 observations (rows) per person.
I want to create three new variables that calculate the difference between the second and first, third and second, and fourth and third rows.
I think retain can do this, but I'm not sure how.
Or do I need an array?
Thanks!
data test;
input person var;
datalines;
1 5
1 10
1 12
1 20
2 1
2 3
2 5
2 90
;
run;
data test;
set test;
by person notsorted;
retain pos;
array diffs{*} diff0-diff3;
retain diff0-diff3;
if first.person then do;
pos = 0;
end;
pos + 1;
diffs{pos} = dif(var);
if last.person then output;
drop var diff0 pos;
run;
Why not use The Lag function.
data test; input person var;
cards;
1 5
1 10
1 12
1 20
2 1
2 3
2 5
2 90
run;
data test; set test;
by person;
LagVar=Lag(Var);
difference=var-Lagvar;
if first.person then difference=.;
run;
An alternative approach without arrays.
/*-- Data from simonn's answer --*/
data SO1019005;
input person var;
datalines;
1 5
1 10
1 12
1 20
2 1
2 3
2 5
2 90
;
run;
/*-- Why not just do a transpose? --*/
proc transpose data=SO1019005 out=NewData;
by person;
run;
/*-- Now calculate your new vars --*/
data NewDataWithVars;
set NewData;
NewVar1 = Col2 - Col1;
NewVar2 = Col3 - Col2;
Newvar3 = Col4 - Col3;
run;
Why not use the dif() function instead?
/* test data */
data one;
do id = 1 to 2;
do v = 1 to 4 by 1;
output;
end;
end;
run;
/* check */
proc print data=one;
run;
/* on lst
Obs id v
1 1 1
2 1 2
3 1 3
4 1 4
5 2 1
6 2 2
7 2 3
8 2 4
*/
/* now create diff within id */
data two;
set one;
by id notsorted; /* assuming already in order */
dif = ifn(first.id, ., dif(v));
run;
proc print data=two;
run;
/* on lst
Obs id v dif
1 1 1 .
2 1 2 1
3 1 3 1
4 1 4 1
5 2 1 .
6 2 2 1
7 2 3 1
8 2 4 1
*/
data output_data;
retain count previous_value diff1 diff2 diff3;
set data input_data
by person;
if first.person then do;
count = 0;
end;
else do;
count = count + 1;
if count = 1 then diff1 = abs(value - previous_value);
if count = 2 then diff2 = abs(value - previous_value);
if count = 3 then do;
diff3 = abs(value - previous_value);
output output_data;
end;
end;
previous_value = value;
run;