Customized printing with PROC REPORT (Chapter 15)
PROC PRINT is fairly limited in terms of how much you can customize
output. PROC REPORT is more difficult to use but also more flexible.
Default behavior is similar to PROC PRINT.
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PROC REPORT
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PROC REPORT
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PROC REPORT
With PROC REPORT, you can specify column widths and use labels for
variables instead of variable names. There are other differences, such as
that the observation number is not included, and there isn’t a blank line
between variable names and the start of the data.
To list which variables you want in the output, you use COLUMN instead
of VAR.
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PROC REPORT
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PROC REPORT
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PROC REPORT: output in SAS Studio
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PROC REPORT: writing to Word file
You can make your output generated by PROC REPORT (or any other
procedure) saved as an .rtf (WORD) file by using the Output Delivery
System. This is also the way to generate PDFs of your graphs from
SGPLOT and similar procedures.
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PROC REPORT: creating Word documents with ODS
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PROC REPORT: creating Word documents with ODS
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PROC REPORT: creating Word documents with ODS
The Word Document isn’t pretty. It has just concatenated the output
from PROC PRINT and PROC REPORT.
SAS seems to fill up the entire width of the Word Document with the
output, so to some extent it ignores the widths that you specify, but the
relative widths for the different columns will still matter.
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Creating .csv files to be read in by Excel
You can also use ODS to create Excel-readable files using a similar
approach. E.g.,
ods csv file="myfile.csv"
proc report data=mydata;
run;
ods csv close;
This is quite useful in consulting situations. You might consult with
someone who wants you to use SAS but doesn’t use SAS themselves. If
they want you to clean up the data and send the processed data back as
an Excel file, this is a good way to do it.
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PROC REPORT
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PROC REPORT
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PROC REPORT
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PROC REPORT: grouping variables
you can also group variables into arbitrary categories.
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PROC REPORT: grouping variables with blanks for
repeated values
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PROC REPORT: computing variables
You can also do computations within PROC REPORT that you would
normally only expect to be able to do within DATA STEPS. The idea here
is to use “Computing Blocks”.
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PROC REPORT: two grouping variables
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PROC REPORT: two grouping variables
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PROC REPORT: two grouping variables
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PROC REPORT: two grouping variables, linux .lst file
Here the BREAK command inserted a line break between levels of
country, which is ignored in SAS Studio and the .rtf file.
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PROC REPORT: two grouping variables, linux .lst file
Changing the order of variables in the COLUMN statement changes the
order in the output (BREAK statement is ignored here in SAS Studio—in
the linux version, the output will be double spaced).
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PROC REPORT: generating subtotals
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PROC REPORT: generating subtotals
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PROC REPORT: generating subtotals
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PROC REPORT: computed variables
You can also do some computation within PROC REPORT instead of
doing it within a datastep by using COMPUTE blocks.
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PROC REPORT: generating summary statistics
Here we sum to get the total number of units sold and their dollar
amounts. You can also get the mean, median or other basic statistics,
rather than the sum.
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PROC REPORT: comments in reports
Sometimes it is useful to have comments which can be long character
strings, such as in a questionaire or comments for a doctor’s visit. In this
case, you can use SPLIT=’ ’ as an option for PROC REPORT and the
FLOW option for the DEFINE statement to allow comments to flow over
to a new line without interfering with other variables.
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PROC REPORT: comments in reports
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PROC REPORT: multicolumn displays
You can use PROC REPORT to display your data in multiple columns,
which can be useful for saving space. Unfortunately I couldn’t get this to
do anything in SAS Studio or the Word document, but it worked in Linux
in the .lst file. Unfortunately, using the ODS to create an .rtf file in
Linux also failed to create multiple columns, so this feature seems to be of
limited use.
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PROC REPORT: multicolumn displays
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PROC REPORT: multicolumn displays
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Multicolumn displays
A place in my life where I have wanted to generate automated
multicolumn displays is in grant proposals or in CVs where I have wanted
to have columns of names of collaborators that are alphabetized by name.
If you change the list of people, it is a pain to change the list of people.
I encountered this problem about a year ago writing grant proposals, so I
came up with a specialized R program to deal with it. Given an input file
with a list of collaborators, it generates the LATEXcode to make a nice little
table of the collaborators in two columns.
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Multicolumn displays: example of lists of collaborators
The main reason for wanting the list to be in two columns is to save
space. Here is what the final output might look like on my CV (biosketch
for NSF, which is required to be at most 2 pages):
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Multicolumn displays: example of lists of collaborators
It is a pain to modify this. If I develop a new collaborator who’s name
doesn’t come later than “Zhu” alphabetically, then I have to insert this
somewhere in the list of names, and this will change the table quite a bit,
so that collaborators will have to be moved from the right to left column
and vice versa. It’s just a pain to do a lot of copying and pasting. If you
apply for several grants per year (I’ve done 8 in the last two years...) and
your list of collaborators is changing rapidly, then you start thinking of
automating the problem.
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Multicolumn displays: collaborator example, plain text data
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Multicolumn displays: collaborator example, plain text data
To make the problem easier for myself, I created a separate column with
the researcher’s last name even though that is repeated with their full
name. I want to alphabetize by last name but display the full name. This
shouldn’t have been necessary, but just made things easier. Here is the R
code to generate the LATEX
jamess-mbp:2013 superjames$ cat collaborators.r
x <- read.table("collaborators.txt",sep=";")
y <- x$V2[order(x$V1)] # sort full names and affiliation by
# lastname
if(length(y) %% 2 == 1) y <- c(y," ") # make even number of cells
y <- matrix(y,ncol=2,byrow=F) # arrange into matrix
write("\\begin{tabular}{ll}",file="collaborators.tex",append=T)
for(i in 1:floor(length(x$V1)/2)) {
write(paste("\\ \\",y[i,1],"&","\\ \\",y[i,2],"\\\\"),file=
"collaborators.tex",append=T)
print(i)
}
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write("\\end{tabular}",file="collaborators.tex",append=T)
Multicolumn displays
It would be reasonably straightforward to do the same sort of thing in SAS
with PROC REPORT except that the minimum page size is 15 lines, so
this is slightly difficult. Here is an attempt.
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Multicolumn displays
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Multicolumn displays
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Multicolumn displays: another attempt in SAS
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Multicolumn displays: another attempt in SAS
Notes: the main reason for using PROC REPORT instead of PROC
PRINT was that I didn’t want the the observation number printed with the
data.
Also, I couldn’t figure out how to get SAS to print \\ at the end of each
line. If you think of a way, let me know!
This is a little tricky because the backslash is a special character in SAS
which sometimes is used for filepaths, sometimes to indicate breaks in
words, but there is usually a way to print special characters in languages,
so I suspect there is a solution.
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Other tips for PROC REPORT
Other features of PROC REPORT are
1. you can sort data within PROC SORT using the ORDER option
within your DEFINE statements (instead of DISPLAY, type ORDER).
This way you don’t have to use a PROC SORT outside of the PROC
REPORT, although this is just a matter of convenience
2. you can also supress printing of a variable even though it is used to
sort the order of the output in the data. For example, it you type
define country / group noprint;
then items will be grouped by country but the country name is not
printed
3. character variables and ranges can be computed within COMPUTE
blocks using logic statements (IF etc.)
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ACROSS variables
When you have two grouping variables, you can make one of them an
ACROSS variable, which essentially turns your report into a 2x2 table.
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ACROSS variables
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ACROSS variables
The comma tells SAS that you want the number of units within each level
of model, instead of reporting the number of units as a separate variable.
Without the comma, it is reporting the number of observations that have
the given combination of model of country, which is 1 for each combination
for this data, and then it gives the marginal total for the number of units.
The use of the comma assumes that you have an ACROSS variable first,
then another non-grouping variable. To transpose the report, do the
following
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ACROSS variables
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RBREAK
RBREAK additionally creates a row of marginal totals.
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Two-way tables
It is a bit more natural to use PROC TABULATE for two-way tables, and
that is what we’ll look at next time...
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