I'm going to ask this with an example...
Suppose i have a data set where each observation represents a person. Two of the variables are AGE and HASADOG (and say this has values 1 for yes and 2 for no.) Is there a way to run a PROC FREQ (by AGE*HASADOG) that forces SAS to include in the report a line for instances where the count is zero?
By this I mean: if there is a particular value for AGE such that no observation with this AGE value has a 1 in the HASADOG variable, the report will still include a row for this combination (with a row percent of 0.)
Is this possible?
The SPARSE option in PROC FREQ is likely all you need.
proc freq data=sashelp.class;
table sex*age / sparse list;
run;
If the value is nowhere in your data set at all, then there's no way for SAS to know it exists. In this case you'd need a more complex solution, basically a way to tell SAS all values you would be using ahead of time. This can be done via a PRELOADFMT or CLASSDATA option on several procs. There are asked an answered questions on this topic here on SO, so I won't provide a solution for this option, which seems beyond the scope of your question.
Related
I just start learning sas and would like some help with understanding the following chunk of code. The following program computes the annual payroll by department.
proc sort data = company.usa out=work.temp;
by dept;
run;
data company.budget(keep=dept payroll);
set work.temp;
by dept;
if wagecat ='S' then yearly = wagrate *12;
else if wagecat = 'H' then yearly = wagerate *2000;
if first.dept then payroll=0;
payroll+yearly;
if last.dept;
run;
Questions:
What does out = work.temp do in the first line of this code?
I understand the data step created 2 temporary variables for each by variable (first.varibale/last.variable) and the values are either 1 or 0, but what does first.dept and last.dept exactly do here in the code?
Why do we need payroll=0 after first.dept in the second to the last line?
This code takes the data for salaries and calculates the payroll amount for each department for a year, assuming salary is the same for all 12 months and that an hourly worker works 2000 hours.
It creates a copy of the data set which is sorted and stored in the work library. RTM.
From the docs
OUT= SAS-data-set
names the output data set. If SAS-data-set does not exist, then PROC SORT creates it.
CAUTION:
Use care when you use PROC SORT without OUT=.
Without the OUT= option, PROC SORT replaces the original data set with the sorted observations when the procedure executes without errors.
Default Without OUT=, PROC SORT overwrites the original data set.
Tips With in-database sorts, the output data set cannot refer to the input table on the DBMS.
You can use data set options with OUT=.
See SAS Data Set Options: Reference
Example Sorting by the Values of Multiple Variables
First.DEPT is an indicator variable that indicates the first observation of a specific BY group. So when you encounter the first record for a department it is identified. Last.DEPT is the last record for that specific department. It means the next record would the first record for a different department.
It sets PAYROLL to 0 at the first of each record. Since you have if last.dept; that means that only the last record for each department is outputted. This code is not intuitive - it's a manual way to sum the wages for people in each department. The common way would be to use a summary procedure, such as MEANS/SUMMARY but I assume they were trying to avoid having two passes of the data. Though if you're not sorting it may be just as fast anyways.
Again, RTM here. The SAS documentation is quite thorough on these beginner topics.
Here's an alternative method that should generate the exact same results but is more intuitive IMO.
data temp;
set company.usa;
if wagecat='S' then factor=12; *salary in months;
else if wagecat='H' then factor=2000; *salary in hours;
run;
proc means data=temp noprint NWAY;
class dept;
var wagerate;
weight factor;
output out=company.budget sum(wagerate)=payroll;
run;
I am using proc tabulate to create an output dataset with statistics (n mean std min max p25 p75 median) for a variable with a long name (close to the 32 character maximum). The output dataset will add _n, _std, etc to our variable name, but the median variable is just named "Median" because the variable name with "_median" added to the end, the resulting variable name would be >32 characters.
Is there a way to specify the name of the variables in the output dataset from within the proc tabulate step? I am looping through 1000s of variable for this procedure, so it's not feasible to rename each variable in a data step. Also, it must be proc tabulate and not proc freq because we need to output a row for every possible value of each variable, not just those values that exist in the data.
proc tabulate data=DATA out=OUT ;
var VERY_LONG_VARIABLE_NAME;
table VERY_LONG_VARIABLE_NAME *(n mean std min max p25 p75 median)/printmiss;
run;
Unfortunately I don't know of a way to override the tabulate names. Even transposing the tabulate doesn't fix that - you still get the same result, sadly.
My suggestion is to use a different proc. Almost all of the procs you might use have a way to get what you want - the PRINTMISS equivalent; for example, PROC FREQ has the SPARSE option which does basically the same thing (despite its odd name), and PROC SUMMARY or PROC MEANS might be even better (with COMPLETETYPES on the class statement), just depending on your data.
Alternately, you could reshape your data, or reshape your process. For example, if you're really looping through thousands of variables, that's horribly inefficient; better would be to reshape to variable|value structure (vertical) and then do one proc tabulate; that would fix your issue right there (as it would make 'varname' be a CLASS or BY variable itself not a contributor to the output variable name) and make your process faster.
You could also add a VIEW step before the tabulate that performs the rename for you; that would cost very little even in a macro loop.
Either way, supply some sample data and an example of the total process you're doing and likely you can get a better answer.
I have the following code:
ods tagsets.excelxp file = 'G:\CPS\myworkwithoutmissing.xml'
style = printer;
proc tabulate data = final;
Class Year Self_Emp_Inc Self_Emp_Uninc Self_Emp Multi_Job P_Occupation Full_Part_Time_Status;
table Year, P_Occupation*n;
table Year, (P_Occupation*Self_Emp_Inc)*n;
table Year, (Self_Emp_Inc*P_Occupation)*n;
run;
ods tagsets.excelxp close;
When I run this code, I get the following error message:
WARNING: A class, frequency, or weight variable is missing on every observation.
WARNING: A class, frequency, or weight variable is missing on every observation.
WARNING: A class, frequency, or weight variable is missing on every observation.
Now in order to circumvent this issue, I add the "missing" option at the end of the class statement such that:
class year self_emp_inc ....... Full_Part_Time_Status/ missing;
This fixes the problem in that it doesn't give me the error message and creates the table. However, my chart now also counts the number of missing values, something that I do not want. For example my variable self_emp_inc has values of 1 and .(for missing). Now when I run the code with the missing option,I get a count of P_Occupation for all the missing values as well, but I only want the count for when the value of self_emp_Inc is 1. How can I accomplish that task?
This is one of those frustrating things in SAS that for some reason SAS hasn't given us a "good" option to work around. Depending on what you're working with, there are a few solutions.
The real problem here is not that you have missings - in a 1x1 table (1 var by 1 var), excluding missings is what you want. It's because you're calling for multiple tables and each table is affected by missings in the class variables in the other table.
As such, oftentimes the easiest answer is simply to split the tables into multiple proc tabulate statements. This might occasionally be too complicated or too onerous in terms of runtime, but I suspect the majority of the time this is the best solution - it often is for me, anyway.
Since you're only working with n, you could instead construct the tabulation with the missings, output to a dataset, then filter them out and re-print or export that dataset. That's the easiest solution, typically.
How exactly you want to do this of course depends on what exactly you want. For example:
data test_cars;
set sashelp.cars;
if _n_=5 then call missing(make);
if _n_=7 then call missing(model);
if _n_=10 then call missing(type);
if _n_=13 then call missing(origin);
run;
proc tabulate data=test_cars out=test_tabulate(rename=n=count);
class make model type origin/missing;
tables (make model type),origin*n;
run;
data test_tabulate_want;
set test_tabulate;
if cmiss(of make model type origin)>2 then delete;
length colvar $200;
colvar = coalescec(of make model type);
run;
proc tabulate data=test_tabulate_want missing;
class colvar origin/order=data;
var count;
tables colvar,origin*count*sum;
run;
This isn't perfect, though it can be made a lot better with some more work on the formatting - this is just a quick example.
If you're using percents, of course, this doesn't exactly work. You either need to refactor the percents in that data step - which is a bit of work, but doable - or you need separate tabulates for each class variable.
This might be a weird question. I have a data set contains data like agree, neutral, disagree...for many questions. There is not so many observations so for some question, one or more options has frequency of 0, say neutral. When I run proc freq, since neutral shows up in that variable, the table does not contain a row for neutral. I end up with tables with different number of rows. I would like to know if there is a option to show these 0 frequency rows. I will also need to run proc gchart for the same data set, and I will run into the same problem for having different number of bars. Please help me on this. Thank you!
This depends on how exactly you are running your PROC FREQ. It has the sparse option, which tells it to create a value for every logical cell on the table when creating an output dataset; normally, while you would have a cell with a missing value (or zero) in a crosstab, if that is output to a dataset (which is vertical, ie each combination of x and y axis value are placed in one row) those rows are left off. Sparse makes sure that doesn't happen; and in a larger (n-dimensional) crosstab, it creates rows for every possible combination of every variable, even ones that don't occur in the data.
However, if you're just doing
proc freq data=mydata;
tables myvar;
run;
That won't help you, as SAS doesn't really have anything to go on to figure out what should be there.
For that, you have to use a class variable procedure. Proc Tabulate is one of such procedures, and is similar to Proc Freq in its syntax (sort of). You need to either use CLASSDATA on the proc statement, or PRINTMISS on the table statement. In the former case, you do not need to use a format, I don't believe. In the latter case (PRINTMISS), you need to create a format for your variable (if you don't already have one) that contains all levels of the data that you want to display (even if it's just an identity format, e.g. formatting character strings to identical character strings), and specify PRELOADFMT on the proc statement. See this man page for more details.
(first time posting)
I have a data set where I need to create a new variable (in SAS), based on meeting a condition related to another variable. So, the data contains three variables from a survey: Site, IDnumb (person), and Date. There can be multiple responses from different people but at the same site (see person 1 and 3 from site A).
Site IDnumb Date
a 1 6/12
b 2 3/4
c 4 5/1
a 3 .
d 5 .
I want to create a new variable called Complete, but it can't contain duplicates. So, when I go to proc freq, I want site A to be counted once, using the 6/12 Date of the Completed Survey. So basically, if a site is represented twice and contains a Date in one, I want to only count that one and ignore the duplicate site without a date.
N %
Complete 3 75%
Last Month 1 25%
My question may be around the NODUP and NODUPKEY possibilities. If I do a Proc Sort (nodupkey) by Site and Date, would that eliminate obs "a 3 ."?
Any help would be greatly appreciated. Sorry for the jumbled "table", as this is my first post (hints on making that better are also welcomed).
You can do this a number of ways.
First off, you need a complete/not complete binary variable. If you're in the datastep anyway, might as well just do it all there.
proc sort data=yourdata;
by site date descending;
run;
data yourdata_want;
set yourdata;
by site date descending;
if first.site then do;
comp = ifn(date>0,1,0);
output;
end;
run;
proc freq data=yourdata_want;
tables comp;
run;
If you used NODUPKEY, you'd first sort it by SITE DATE DESCENDING, then by SITE with NODUPKEY. That way the latest date is up top. You also could format COMP to have the text labels you list rather than just 1/0.
You can also do it with a format on DATE, so you can skip the data step (still need the sort/sort nodupkey). Format all nonmissing values of DATE to "Complete" and missing value of date to "Last Month", then include the missing option in your proc freq.
Finally, you could do the table in SQL (though getting two rows like that is a bit harder, you have to UNION two queries together).