Here are my results. Since PPD has a missing result I'd like to eliminate all results for PPD. I.e. I'd like to eliminate all records where ticker='PPD' if any record where ticker='PPD' has a missing result (corr).
How can I program this in SAS? I don't want to just eliminate that missing observation but eliminate PPD altogether. Thanks.
Ticker Day Corr
PPD 7 -1
PPD 8
PTP 7 0.547561231
PTP 8 0.183279038
Lots of ways to do this, and what is most efficient depends on your data. If you don't have too much data, then I'd use the easiest method that fits with your knowledge and other habits.
*SQL delete;
proc sql;
delete from have H where exists (
select 1 from have V where H.ticker=V.ticker and V.corr is null);
quit;
*FREQ for missing (or means or whatever) then delete from that;
*Requires have to be sorted.;
proc freq data=have;
tables ticker*corr/missing out=ismiss(where=(missing(corr)));
run;
data want;
merge have(in=_h) ismiss(in=_m);
by ticker;
if _h and not _m;
run;
*double DoW. Requires either dataset is sorted by ticker,;
*or requires it to be organized by ticker (but tickers can be not alphabetically sorted); *and use norsorted on by statement;
data want;
do _n_=1 by 1 until (last.ticker);
set have;
by ticker;
if missing(corr) then _miss=1;
end;
do _n_=1 by 1 until (last.ticker);
set have;
by ticker;
if _miss ne 1 then output;
end;
run;
This is easily accomplished in PROC SQL...
proc sql ;
create table to_delete as
select distinct ticker
from mydata
where missing(corr) ;
delete from mydata
where ticker in(select ticker from to_delete) ;
quit ;
Unfortunately, it can't be done in a single SQL step as the delete from statement would recursively reference the source dataset.
Related
I have the following table
Row1, 3
Row2, 5
Row3, 8
and I now want to sum over all rows and place the result as a new variable on all rows, i.e.
Row1, 3, SUM(Row1,Row2,Row3)
Row2, 5, SUM(Row1,Row2,Row3)
Row3, 8, SUM(Row1,Row2,Row3)
Just like sum in proc sql would work... I've tried the simple sum, but that only sums the row. Any tips?
First: the SQL solution, or the PROC solution (where you run PROC MEANS to get the sum and then just incorporate it), is generally substantially preferred to the data step solution in most cases. Using built-in tools is typically better than writing your own tool to replicate something already extant.
However, the data step solution isn't terribly complicated. You just need to use what's known colloquially as a DoW loop (after two of the people who popularized it) and iterate over the dataset twice, once to get the sums and then the second time to output the rows. You can adapt this easily to summing over by-groups by changing until(eof) to until(last.byvar) (byvar being whatever by variable you are summing over) and adding a by group with that byvar inside both of the loops.
data want;
do _n_ = 1 by 1 until (eof);
set sashelp.class end=eof;
sumvar = sum(sumvar,age);
end;
do _n_ = 1 by 1 until (eof1);
set sashelp.class end=eof1;
output;
end;
run;
A SQL sum will accomplish this and merge it back in to the dataset automatically.
You will see a note in the LOG regarding merging the data.
PROC SQL;
Create table want as
Select *, sum(variable2sum) as total
From have;
Quit;
EDIT:
Since SQL wasn't an option, a more common answer is to create the sum in proc means and merge it in. Here's the code for that solution as well:
proc means data=sashelp.class noprint;
output out=summary mean(age)=avg_age;
run;
data class;
set sashelp.class;
if _n_=1 then
set summary;
drop _type_ _freq_;
run;
proc print data=class;
run;
What i want to do: I need to create a new variables for each value labels of a variable and do some recoding. I have all the value labels output from a SPSS file (see sample).
Sample:
proc format; library = library ;
value SEXF
1 = 'Homme'
2 = 'Femme' ;
value FUMERT1F
0 = 'Non'
1 = 'Oui , occasionnellement'
2 = 'Oui , régulièrement'
3 = 'Non mais j''ai déjà fumé' ;
value ... (many more with different amount of levels)
The new variable name would be the actual one without F and with underscore+level (example: FUMERT1F level 0 would become FUMERT1_0).
After that i need to recode the variables on this pattern:
data ds; set ds;
FUMERT1_0=0;
if FUMERT1=0 then FUMERT1_0=1;
FUMERT1_1=0;
if FUMERT1=1 then FUMERT1_1=1;
FUMERT1_2=0;
if FUMERT1=2 then FUMERT1_2=1;
FUMERT1_3=0;
if FUMERT1=3 then FUMERT1_3=1;
run;
Any help will be appreciated :)
EDIT: Both answers from Joe and the one of data_null_ are working but stackoverflow won't let me pin more than one right answer.
Update to add an _ underscore to the end of each name. It looks like there is not option for PROC TRANSREG to put an underscore between the variable name and the value of the class variable so we can just do a temporary rename. Create rename name=newname pairs to rename class variable to end in underscore and to rename them back. CAT functions and SQL into macro variables.
data have;
call streaminit(1234);
do caseID = 1 to 1e4;
fumert1 = rand('table',.2,.2,.2) - 1;
sex = first(substrn('MF',rand('table',.5),1));
output;
end;
stop;
run;
%let class=sex fumert1;
proc transpose data=have(obs=0) out=vnames;
var &class;
run;
proc print;
run;
proc sql noprint;
select catx('=',_name_,cats(_name_,'_')), catx('=',cats(_name_,'_'),_name_), cats(_name_,'_')
into :rename1 separated by ' ', :rename2 separated by ' ', :class2 separated by ' '
from vnames;
quit;
%put NOTE: &=rename1;
%put NOTE: &=rename2;
%put NOTE: &=class2;
proc transreg data=have(rename=(&rename1));
model class(&class2 / zero=none);
id caseid;
output out=design(drop=_: inter: rename=(&rename2)) design;
run;
%put NOTE: _TRGIND(&_trgindn)=&_trgind;
First try:
Looking at the code you supplied and the output from Joe's I don't really understand the need for the formats. It looks to me like you just want to create dummies for a list of class variables. That can be done with TRANSREG.
data have;
call streaminit(1234);
do caseID = 1 to 1e4;
fumert1 = rand('table',.2,.2,.2) - 1;
sex = first(substrn('MF',rand('table',.5),1));
output;
end;
stop;
run;
proc transreg data=have;
model class(sex fumert1 / zero=none);
id caseid;
output out=design(drop=_: inter:) design;
run;
proc contents;
run;
proc print data=design(obs=40);
run;
One good alternative to your code is to use proc transpose. It won't get you 0's in the non-1 cells, but those are easy enough to get. It does have the disadvantage that it makes it harder to get your variables in a particular order.
Basically, transpose once to vertical, then transpose back using the old variable name concatenated to the variable value as the new variable name. Hat tip to Data null for showing this feature in a recent SAS-L post. If your version of SAS doesn't support concatenation in PROC TRANSPOSE, do it in the data step beforehand.
I show using PROC EXPAND to then set the missings to 0, but you can do this in a data step as well if you don't have ETS or if PROC EXPAND is too slow. There are other ways to do this - including setting up the dataset with 0s pre-proc-transpose - and if you have a complicated scenario where that would be needed, this might make a good separate question.
data have;
do caseID = 1 to 1e4;
fumert1 = rand('Binomial',.3,3);
sex = rand('Binomial',.5,1)+1;
output;
end;
run;
proc transpose data=have out=want_pre;
by caseID;
var fumert1 sex;
copy fumert1 sex;
run;
data want_pre_t;
set want_pre;
x=1; *dummy variable;
run;
proc transpose data=want_pre_t out=want delim=_;
by caseID;
var x;
id _name_ col1;
copy fumert1 sex;
run;
proc expand data=want out=want_e method=none;
convert _numeric_ /transformin=(setmiss 0);
run;
For this method, you need to use two concepts: the cntlout dataset from proc format, and code generation. This method will likely be faster than the other option I presented (as it passes through the data only once), but it does rely on the variable name <-> format relationship being straightforward. If it's not, a slightly more complex variation will be required; you should post to that effect, and this can be modified.
First, the cntlout option in proc format makes a dataset of the contents of the format catalog. This is not the only way to do this, but it's a very easy one. Specify the appropriate libname as you would when you create a format, but instead of making one, it will dump the dataset out, and you can use it for other purposes.
Second, we create a macro that performs your action one time (creating a variable with the name_value name and then assigning it to the appropriate value) and then use proc sql to make a bunch of calls to that macro, once for each row in your cntlout dataset. Note - you may need a where clause here, or some other modifications, if your format library includes formats for variables that aren't in your dataset - or if it doesn't have the nice neat relationship your example does. Then we just make those calls in a data step.
*Set up formats and dataset;
proc format;
value SEXF
1 = 'Homme'
2 = 'Femme' ;
value FUMERT1F
0 = 'Non'
1 = 'Oui , occasionnellement'
2 = 'Oui , régulièrement'
3 = 'Non mais j''ai déjà fumé' ;
quit;
data have;
do caseID = 1 to 1e4;
fumert1 = rand('Binomial',.3,3);
sex = rand('Binomial',.5,1)+1;
output;
end;
run;
*Dump formats into table;
proc format cntlout=formats;
quit;
*Macro that does the above assignment once;
%macro spread_var(var=, val=);
&var._&val.= (&var.=&val.); *result of boolean expression is 1 or 0 (T=1 F=0);
%mend spread_var;
*make the list. May want NOPRINT option here as it will make a lot of calls in your output window otherwise, but I like to see them as output.;
proc sql;
select cats('%spread_var(var=',substr(fmtname,1,length(Fmtname)-1),',val=',start,')')
into :spreadlist separated by ' '
from formats;
quit;
*Actually use the macro call list generated above;
data want;
set have;
&spreadlist.;
run;
I have multiple tables in a library call snap1:
cust1, cust2, cust3, etc
I want to generate a loop that gets the records' count of the same column in each of these tables and then insert the results into a different table.
My desired output is:
Table Count
cust1 5,000
cust2 5,555
cust3 6,000
I'm trying this but its not working:
%macro sqlloop(data, byvar);
proc sql noprint;
select &byvar.into:_values SEPARATED by '_'
from %data.;
quit;
data_&values.;
set &data;
select (%byvar);
%do i=1 %to %sysfunc(count(_&_values.,_));
%let var = %sysfunc(scan(_&_values.,&i.));
output &var.;
%end;
end;
run;
%mend;
%sqlloop(data=libsnap, byvar=membername);
First off, if you just want the number of observations, you can get that trivially from dictionary.tables or sashelp.vtable without any loops.
proc sql;
select memname, nlobs
from dictionary.tables
where libname='SNAP1';
quit;
This is fine to retrieve number of rows if you haven't done anything that would cause the number of logical observations to differ - usually a delete in proc sql.
Second, if you're interested in the number of valid responses, there are easier non-loopy ways too.
For example, given whatever query that you can write determining your table names, we can just put them all in a set statement and count in a simple data step.
%let varname=mycol; *the column you are counting;
%let libname=snap1;
proc sql;
select cats("&libname..",memname)
into :tables separated by ' '
from dictionary.tables
where libname=upcase("&libname.");
quit;
data counts;
set &tables. indsname=ds_name end=eof; *9.3 or later;
retain count dataset_name;
if _n_=1 then count=0;
if ds_name ne lag(ds_name) and _n_ ne 1 then do;
output;
count=0;
end;
dataset_name=ds_name;
count = count + ifn(&varname.,1,1,0); *true, false, missing; *false is 0 only;
if eof then output;
keep count dataset_name;
run;
Macros are rarely needed for this sort of thing, and macro loops like you're writing even less so.
If you did want to write a macro, the easier way to do it is:
Write code to do it once, for one dataset
Wrap that in a macro that takes a parameter (dataset name)
Create macro calls for that macro as needed
That way you don't have to deal with %scan and troubleshooting macro code that's hard to debug. You write something that works once, then just call it several times.
proc sql;
select cats('%mymacro(name=',"&libname..",memname,')')
into :macrocalls separated by ' '
from dictionary.tables
where libname=upcase("&libname.");
quit;
¯ocalls.;
Assuming you have a macro, %mymacro, which does whatever counting you want for one dataset.
* Updated *
In the future, please post the log so we can see what is specifically not working. I can see some issues in your code, particularly where your macro variables are being declared, and a select statement that is not doing anything. Here is an alternative process to achieve your goal:
Step 1: Read all of the customer datasets in the snap1 library into a macro variable:
proc sql noprint;
select memname
into :total_cust separated by ' '
from sashelp.vmember
where upcase(memname) LIKE 'CUST%'
AND upcase(libname) = 'SNAP1';
quit;
Step 2: Count the total number of obs in each data set, output to permanent table:
%macro count_obs;
%do i = 1 %to %sysfunc(countw(&total_cust) );
%let dsname = %scan(&total_cust, &i);
%let dsid=%sysfunc(open(&dsname) );
%let nobs=%sysfunc(attrn(&dsid,nobs) );
%let rc=%sysfunc(close(&dsid) );
data _total_obs;
length Member_Name $15.;
Member_Name = "&dsname";
Total_Obs = &nobs;
format Total_Obs comma8.;
run;
proc append base=Total_Obs
data=_total_obs;
run;
%end;
proc datasets lib=work nolist;
delete _total_obs;
quit;
%mend;
%count_obs;
You will need to delete the permanent table Total_Obs if it already exists, but you can add code to handle that if you wish.
If you want to get the total number of non-missing observations for a particular column, do the same code as above, but delete the 3 %let statements below %let dsname = and replace the data step with:
data _total_obs;
length Member_Name $7.;
set snap1.&dsname end=eof;
retain Member_Name "&dsname";
if(NOT missing(var) ) then Total_Obs+1;
if(eof);
format Total_Obs comma8.;
run;
(Update: Fixed %do loop in step 2)
I have a bunch of sas datasets of various lengths and I need to trim the nth highest and lowest values by a variable value.
To do this for when I needed to trim the highest and lowest I did this
DATA VDBP273_first_night_Systolic;
SET VDBP273_first_night end=eof;
IF _N_ =1 then delete;
if eof then delete;
run;
And it worked fine.
Now I need to do something more like this
PROC SORT DATA=foo OUT=foo_sorted;
BY bar;
run;
DATA foo_out;
SET foo_sorted end=eof;
IF _N_ <= 5 then delete;
if eof *OR THE 4 right before it* then delete;
run;
I'm sure this is easy but it's stumping me. How can I say the last 5 of this sorted data set delete those?
Since you are presorting your data and then trying to eliminate top n and bottom n record, You can easily solve your problem using OBS= and FIRSTOBS= dataset option.
proc sql noprint;
select count(*) -4 into:counter from sashelp.class ;
quit;
proc sort data=sashelp.class out=have;by height;run;
proc print data=have;run;
data want;
set have(firstobs=6 obs=&counter);
run;
proc print data=want;run;
You can use the nobs= dataset option to store the total number of observations, which then means you can do something similar to your code to exclude the top/bottom n records.
I'd recommend putting the number of records to be excluded in a macro variable, it makes it easier to read and change than hard coding it.
%let excl = 6;
data want;
set sashelp.class nobs=numobs;
if &excl.< _n_ <=(numobs-&excl.);
run;
or simply do the same step done before, adding descending to the proc sort variable
proc sort data=have out=want; by var1 descending; run;
I have a data set of patient information where I want to count how many patients (observations) have a given diagnostic code. I have 9 possible variables where it can be, in diag1, diag2... diag9. The code is V271. I cannot figure out how to do this with the "WHERE" clause or proc freq.
Any help would be appreciated!!
Your basic strategy to this is to create a dataset that is not patient level, but one observation is one patient-diagnostic code (so up to 9 observations per patient). Something like this:
data want;
set have;
array diag[9];
do _i = 1 to dim(diag);
if not missing(diag[_i]) then do;
diagnosis_Code = diag[_i];
output;
end;
end;
keep diagnosis_code patient_id [other variables you might want];
run;
You could then run a proc freq on the resulting dataset. You could also change the criteria from not missing to if diag[_i] = 'V271' then do; to get only V271s in the data.
An alternate way to reshape the data that can match Joe's method is to use proc transpose like so.
proc transpose data=have out=want(keep=patient_id col1
rename=(col1=diag)
where=(diag is not missing));
by patient_id;
var diag1-diag9;
run;