PROC TABULATE:
CONTROLLING TABLE APPEARANCE:
August V. Treff, NationsBank
appearance of a table by displaying the values for
questions, QUES, versus responses, RESP. The SAS®
code is:
ABSTRACT
PROC TABULATE provides one, two, and three
dimensional tables. Tables may be constructed from
class variables, analysis variables, and statistics
keywords. Descriptive statistics can be displayed in table
format with a minimum of code.
This paper will use a five-response survey to demonstrate
how proc tabulate features translate to a printed report.
We will examine table dimensions, crossing and
concatenating variables, and percent calculations.
Controlling table appearance through formats and
customized column headings also will be discussed.
Many programmers do not use PROC TABULATE
because they find that there is too much to learn about
the procedure. PROC TABULATE has many more
features than other procedures. We will examine the
effect that these features have on the report display.
TABLE APPEARANCE
Tabular reports are defined by the table statement.
Table
page dimension definition,
row dimension definition,
column dimension definition;
Commas are used to separate dimensions. If two
dimensions are specified, they are interpreted as row and
column definitions. One dimension is interpreted as a
column definition. An asterisk is used to nest variables
within a definition while a space concatenates variables.
Our task is to prepare a tabular report of responses to a
ten question survey. Responses have been entered into a
sequential file. Elements include
GENDER (M F),
AGE group (1 to 3),
GROUP code (1 to 3),
LOCATION, and
RESP (responses A through E).
A blank in a field indicates no response while an asterisk
indicates multiple responses. The item number, QUES,
is determined from the position of the response.
We begin our examination of how to control the
- 1 -
Proc Tabulate Data=SURVEY;
Class QUES RESP;
Table QUES,
RESP;
Variables QUES and RESP must be included in a
CLASS statement if they are to be used in a TABLE
statement. QUES serves as the row dimension while
RESP serves as the column dimension.
Our efforts are rewarded with a tabular display of
question numbers crossed with responses.
--------------------------------------------|
|
RESP
|
|------------------------|
|
A
|
B
|
|------------+-----------|
|
N
|
N
|------------------+------------+-----------|QUES
|
|
|------------------|
|
|1
|
167.00|
144.00
|------------------+------------+-----------|2
|
157.00|
144.00
The display of frequencies as two place decimals is not
what is desired. The default format of BEST12. may be
overridden with:
Proc Tabulate FORMAT=5.;
and we get:
------------------------------------------|
|
RESP
|
|----------------------|
| A | B | C | D
|
|-----+-----+-----+----|
| N | N | N | N
|------------------+-----+-----+-----+----|QUES
|
|
|
|
|------------------|
|
|
|
|1
| 167| 144| 281| 245
|------------------+-----+-----+-----+----|2
| 157| 144| 266| 263
In addition to suppressing the decimal places, we have
reduced the width of each cell to five spaces.
Our next area for improving the appearance of the table
is the size of the row title space. By default, this space
is one-fourth of the LINESIZE= value. Its size can be
changed with an option on the TABLE statement.
Table QUES,
RESP / rts=6;
RESP*SUM*_FREQ_ / rts=6;
which gives us the following result:
----------------------------|
|
RESP
|
|----------------------|
| A | B | C | D
|
|-----+-----+-----+----|
| N | N | N | N
|----+-----+-----+-----+----|QUES|
|
|
|
|----|
|
|
|
|1
| 167| 144| 281| 245
|----+-----+-----+-----+----|2
| 157| 144| 266| 263
and our report becomes:
-------------------------|
|
Resp
|
|-------------------|
| *
| A
| B
|
|------+------+-----|
|Count |Count |Count
|
|------+------+-----|
|_FREQ_|_FREQ_|_FREQ_
|----+------+------+-----|Item|
|
|
|----|
|
|
|1
|
10|
166|
145
|----+------+------+-----|2
|
7|
157|
144
The RTS= option changes the size of the row title space.
The vertical lines count as spaces in RTS. This was not
the case when we changed the cell width with
FORMAT=.
The word "Count" replaces "SUM" because of the
keylabel statement. The analysis variable name _FREQ_
may be suppressed by adding the following:
The name of a statistic, such as N, may be relabeled with
a KEYLABEL statement. Class variables may be
relabeled with a LABEL statement.
Keylabel
Label
RESP*SUM*_FREQ_=' ' / rts=6;
N='Count';
QUES='Item'
RESP='Response';
The display becomes:
-------------------------|
|
Resp
|
|-------------------|
| *
| A
| B
|
|------+------+-----|
|Count |Count |Count
|----+------+------+-----|Item|
|
|
|----|
|
|
|1
|
10|
166|
145
|----+------+------+-----|2
|
7|
157|
144
The display becomes:
-----------------------------------|
|
Response
|
|
|-----------------------------|
|
| A | B | C | D | E |
|
|-----+-----+-----+-----+-----|
|
|Count|Count|Count|Count|Count|
|----+-----+-----+-----+-----+-----|
|Item|
|
|
|
|
|
|----|
|
|
|
|
|
|1
| 167| 144| 281| 245| 142|
|----+-----+-----+-----+-----+-----|
|2
| 157| 144| 266| 263| 154|
This feature allows us to suppress the printing of a
column definition variable or statistic.
Adding
_FREQ_=' ' to a label statement would suppress the word
_FREQ_ but the blank cell would remain. Statistic
names may also be suppressed in this manner.
Data may be summarized in a PROC SUMMARY step
before being reported with Proc Tabulate. This uses
fewer resources and results in a shorter run time. In the
PROC TABULATE step, an analysis variable is needed
along with the statistic SUM. The PROC SUMMARY
step is as follows:
Labels may be included between the single quotes. This
allows greater control over labels than do the
KEYLABEL and LABEL statements.
Proc Summary NWAY;
Class QUES RESP;
Output out=SURSUMM;
Total responses to an item may be displayed by adding
the keyword "all" to the column dimension definition.
The TABLE statement is:
The default variable, _FREQ_, provides the frequency of
each crossing of QUES and RESP. _FREQ_ is used as
the analysis variable for PROC TABULATE. Our new
invocation is:
Table QUES,
All*SUM*_FREQ_=' '
RESP*SUM*_FREQ_=' '
/ rts=6;
or
Proc Tabulate data=SURSUMM format=6.;
Class
QUES RESP;
Var
REQ_;
Keylabel sum='Count';
Label
QUES='Item'
RESP='Response';
Table
QUES,
Table QUES,
(All RESP)*SUM*_FREQ_=' '
/ rts=6;
-
Either statement produces:
2 -
--------------------------------------|
|
GENDER
|
|
|--------------------|
|
| *
| F
| M
|
|----------------+------+------+------|
|Item
|Response|
|
|
|
|-------+--------|
|
|
|
|1
|A
|
4|
92|
67|
|
|--------+------+------+------|
|
|B
|
1|
83|
60|
-------------------------|
|
|
|
|
|------------|
| ALL | *
| A
|----+------+------+-----|Item|
|
|
|----|
|
|
|1
|
989|
10|
166
|----+------+------+-----|2
|
991|
7|
157
The row title space is divided evenly between QUES and
RESP columns. Three of the eighteen allotted spaces are
used for delimiter characters "|". The first column is one
character smaller than the second column.
Variable ALL may be relabeled with the KEYLABEL
statement or by using ='text' in the table statement. The
table statement method has the advantage of allowing
different labels for ALL in different contexts, as in:
Values for GENDER are displayed in ASCII sort
sequence by default. The order that variable values are
displayed may be changed by using the ORDER option in
the PROC TABULATE statement. Available options are
DATA, FORMATTED, FREQ, and INTERNAL. DATA
displays values in the order in which they are
encountered in the data set. FORMATTED sorts by the
formatted values. FREQ orders by descending frequency.
Table QUES ALL='Column Total',
(ALL='Row Total'
RESP)*
SUM*_FREQ_=' ';
ALL is separated from RESP by a space. This
concatenates the sums for ALL and each value of RESP.
The use of parentheses allows us to avoid repeating the
code *SUM*_FREQ_=' '.
None of the options will result in the desired display of
Male-Female followed by Invalid. Also, the option is
applied to all variables in the table statement. Using
ORDER=FREQ produces:
Sums for ALL differ because of values of missing for
RESP. Missing values are suppressed unless the missing
option is included in the PROC TABULATE statement.
Proc Tabulate data=SURSUMM
format=6. missing;
--------------------------------------|
|
GENDER
|
|
|--------------------|
|
| F
| M
| *
|
|----------------+------+------+------|
|Item
|Response|
|
|
|
|-------+--------|
|
|
|
|1
|C
|
152|
122|
2|
|
|--------+------+------+------|
|
|D
|
126|
114|
4|
|
|--------+------+------+------|
The missing statement must also be included in any
preceding PROC SUMMARY. Our display becomes:
--------------------------------|
|
|
|
| Row |-------------------|
|Total |
| *
| A
|----+------+------+------+-----|Item|
|
|
|
|----|
|
|
|
|1
| 1000|
11|
10|
166
|----+------+------+------+-----|2
| 1000|
9|
7|
157
The order in which GENDER values are displayed can
best be controlled by recoding "M" as "0", "F" as "1", and
invalid responses as "3". The display of these values may
then be modified with a format. We code a PROC
FORMAT step as follows:
More complicated tables may be produced using the
asterisk to nest variables within a dimension definition.
We may want to display the item numbers along with the
responses along the side. Gender will be displayed across
the top of the table. We will use only responses of A
through E in our analysis by including the statement
Proc Format;
Value $sex 'M'='0'
‘F'='1'
other='3';
Value $gen '0'='Male'
'1'='Female'
'3'='Invalid';
If 'A'<=RESP<='E' then output;
In the DATA-step. we code:
in our DATA-step.
GENDER = put(GENDER,$sex.);
The TABLE statement:
Our PROC TABULATE step then becomes:
Table QUES*RESP,
GENDER*SUM*_FREQ_=' '
/rts=18;
Proc Tabulate format=6.;
Class QUES RESP GENDER;
Var
FREQ_;
Keylabel SUM='Count';
produces this display:
-
3 -
Class QUES RESP GENDER AGE;
Format GENDER $gen. AGE $age.;
Label
QUES='Item'
RESP='Response';
Table QUES*RESP,
GENDER*SUM=' '*_FREQ_=' '
/ rts=18;
Format GENDER $gen.;
The TABLE-Statement becomes:
Table QUES*RESP,
(GENDER AGE)*SUM*_FREQ_=' '
/ rts=18;
The printed report becomes:
--------------------------------------|
|
GENDER
|
|
|--------------------|
|
|
|
|Inval-|
|
| Male |Female| id |
|----------------+------+------+------|
|Item
|Response|
|
|
|
|-------+--------|
|
|
|
|1
|A
|
67|
92|
7|
|
|--------+------+------+------|
|
|B
|
60|
83|
2|
|
|--------+------+------+------|
|
|C
|
122|
152|
3|
Our display becomes:
---------------------------------------|
|
AGE
|
GENDER
|----------------------|---------------| Under | 21 to |
| Male |Female | 21
| 50
|Over 50
+-------+-------+-------+-------+------|
|
|
|
|
|
|
|
|
|
|
67|
92|
12|
90|
57
+-------+-------+-------+-------+------|
60|
83|
6|
93|
44
The desired order is achieved. Because of the way in
which we reassigned values for GENDER, both space
and asterisk are tallied as "Invalid".
Inserting an asterisk between GENDER and AGE in the
table statement will nest AGE within GENDER. The
display will be a cross of GENDER and AGE.
The text "Invalid" did not fit into the six spaces allowed.
PROC TABULATE will automatically divide headers
where spaces or hyphens occur. It will not suppress the
hyphen if the label fits in the allotted space. Changing
the value in the PROC FORMAT step to '3'='In-valid'
produces:
Table QUES*RESP,
GENDER*AGE*SUM*_FREQ_=' '
/ rts=18;
which then gives the result below:
------------------------------------------|
GENDER
|-----------------------------------------|
Male
|
Female
|-----------------------+-----------------|
AGE
|
AGE
|-----------------------+-----------------| Under | 21 to |
| Under | 21 to |
| 21
| 50
|Over 50| 21
| 50
|Ov
+-------+-------+-------+-------+-------+-|
|
|
|
|
|
|
|
|
|
|
|
|
3|
33|
31|
9|
57|
+-------+-------+-------+-------+-------+-|
2|
40|
18|
4|
53|
---------------------|
GENDER
|
|--------------------|
|
|
| In- |
| Male |Female|valid |
+------+------+------|
Although this is an improved division for the word
"Invalid", a better solution is to increase the default
format by one space as in:
Proc Tabulate format=7.;
Subtotals can be produced by adding the keyword ALL
after the appropriate class variable.
This gives us:
------------------------|
GENDER
|
|-----------------------|
| Male |Female |Invalid|
+-------+-------+-------|
Table QUES*RESP,
GENDER*(AGE all='All Ages')*
SUM*_FREQ_=' '
/ rts=18;
Variables may be concatenated in the column dimension
definition.
We might want to display response
distributions by GENDER and then by AGE. The values
of AGE, one through three, are associated with a format
“$age.”.
which produces table below.
---------------------------------------|
GENDER
|--------------------------------------|
Male
|
|-------------------------------+------|
AGE
|
|
|-----------------------|
|------| Under | 21 to |
| All | Under
| 21
| 50
|Over 50| Ages | 21
+-------+-------+-------+-------+------|
|
|
|
|
|
|
|
|
|
Value $age '1'='Under 21'
'2'='21 to 50'
'3'='Over 50';
AGE is added to the CLASS and FORMAT statements.
-
4 -
Table
LOC='Location',
QUES*RESP,
GENDER=' '*sum=' '*_FREQ_=' '
/ rts=18 box='July ''97 Survey';
|
3|
33|
31|
67|
9
+-------+-------+-------+-------+------|
2|
40|
18|
60|
4
The variable names GENDER and AGE do not
contribute to the readability of the report. Their printing
may be suppressed with the addition of =' ' in the
TABLE statement. Our display becomes:
The resulting report is:
Location 701
---------------------------------|July '97 Survey | Male |Female |
|----------------+-------+-------|
|Item
Response|
|
|
|1
A
|
26|
33|
|
B
|
15|
19|
|
C
|
44|
52|
|
D
|
36|
50|
|
E
|
25|
34|
---------------------------------------|
Male
|
|-------------------------------+------| Under | 21 to |
| All | Under
| 21
| 50
|Over 50| Ages | 21
+-------+-------+-------+-------+------|
|
|
|
|
|
|
|
|
|
|
3|
33|
31|
67|
9
+-------+-------+-------+-------+------|
2|
40|
18|
60|
4
Text which does not fit in the box is truncated. When
box=_page_ is used, the page dimension text is printed
in the box.
Adding the NOSEPS option to the PROC TABULATE
statement will suppress the horizontal lines below the
headers. This option allows more lines to be printed on
one page. The revised report becomes:
---------------------------------|Location 701
| Male |Female |
|----------------+-------+-------|
|Item
Response|
|
|
|1
A
|
26|
33|
|
B
|
15|
19|
|
C
|
44|
52|
-------------------------------------------|
|
Male
|
|-------------------------|
| Under | 21 to |
|
|
| 21
| 50
|Over 50| A
|----------------+-------+-------+-------+-|Item
Response|
|
|
|
|1
A
|
3|
33|
31|
|
B
|
2|
40|
18|
|
C
|
4|
83|
35|
A fourth table dimension became available when version
6 of SAS allowed the printing of by variables in titles.
More than one table may be printed on a physical page by
adding the CONDENSE option to the table statement.
Invoking the option NOBYLINE and using the physical
page variable in the TITLE and the BY statement will
result in multiple short tables being printed on a physical
page. The code is:
Also suppressed is the vertical separator in the row title
space.
A third dimension is available with PROC TABULATE..
This dimension, the page dimension, is the first
definition when three are included in the TABLE
statement. We could provide reports by location with the
following TABLE statement:
Options nobyline;
Title
'Population at Location ##byval(LOC)';
Proc Tabulate noseps format=6.;
Class GENDER GROUP AGE;
Var _FREQ_;
By LOC;
Table
GENDER,
AGE,
GROUP*SUM=' '*_FREQ_=' '
/ rts=18 box=_page_ condense;
Format GENDER $gen.
GROUP $grp.
AGE $age.;
Table
LOC='Location',
QUES*RESP,
GENDER=' '*sum=' '*_FREQ_=' '
/ rts=18;
LOC is also added to the CLASS statement. Our report
becomes:
Location 701
---------------------------------|
| Male |Female |
|----------------+-------+-------|
|Item
Response|
|
|
|1
A
|
26|
33|
|
B
|
15|
19|
A page of the resulting report is:
Population at Location #701
-----------------------------------------|GENDER Male
|
GROUP
|
|
|-----------------------|
|
| Sales | R & D | Other |
|----------------+-------+-------+-------|
|AGE
|
|
|
|
The box at the upper left corner of the table may be used
in two ways. Text may be inserted using the TABLE
state- ment.
-
5 -
QUES,
RESP*sum=' '*_FREQ_=' '
/ rts=6 printmiss;
|Under 21
|
10|
39|
.|
|21 to 50
|
315|
356|
254|
|Over 50
|
208|
227|
47|
----------------------------------------------------------------------------------|GENDER Female
|
GROUP
|
|
|-----------------------|
|
| Sales | R & D | Other |
|----------------+-------+-------+-------|
|AGE
|
|
|
|
|Under 21
|
39|
30|
10|
|21 to 50
|
479|
493|
244|
|Over 50
|
216|
234|
145|
------------------------------------------
The resulting table displays values of missing under
response B for location #703.
Location 703
---------------------------------------------|
|
Response
|
|
|--------------------------------------|
|
|
A
|
B
|
C
|
D
|
E
|
|----+-------+-------+-------+-------+-------|
|Item|
|
|
|
|
|
|----|
|
|
|
|
|
|1
|
6|
.|
13|
4|
2|
|----+-------+-------+-------+-------+-------|
|2
|
9|
.|
4|
9|
3|
Location #702 has no males represented in survey
responses. The physical page for #702 would be as
follows:
Population at Location #702
-----------------------------------------|GENDER Female
|
GROUP
|
|
|-----------------------|
|
| Sales | R & D | Other |
|----------------+-------+-------+-------|
|AGE
|
|
|
|
|Under 21
|
88|
108|
30|
|21 to 50
|
879|
976|
461|
|Over 50
|
379|
357|
266|
------------------------------------------
It is possible that no one in the population selected B for
any question. We would like to have a column printed
for B with missing values. To accomplish this, we need
to inform PROC TABULATE that B is a valid answer.
One way to accomplish this is to read the text of
questions and responses from a keyed file. This file of
valid responses would be merged with the data set
created by the PROC SUMMARY step.
Data should be sorted by the by variable. Alternatively,
NOTSORTED may be added to the by statement.
Data VALID;
Merge SURSUMM QUESTS;
By QUES RESP;
If _FREQ_ = . then LOC='701';
When a value is not represented in a table, PROC
TABULATE does not include the value in the table. At
location #703, no one selected response B for any
question. When we report the cross of LOC, QUES, and
RESP with the following code:
Any crossing of QUES and RESP which was not
represented in the data set SURSUMM would have a
value of missing for _FREQ_. Assigning a valid value
for LOC avoids producing a table for missing LOC. We
produce the desired tables with a combination of the
MISSING and PRINTMISS options:
Proc Tabulate format=7.;
Class LOC QUES RESP;
Var _FREQ_;
Label QUES='Item' RESP='Response';
Table LOC='Location',
QUES,
RESP*sum=' '*_FREQ_=' '
/ rts=6;
Proc Tabulate format=7. missing;
Class LOC QUES RESP;
Var _FREQ_;
Label QUES='Item' RESP='Response';
Table LOC='Location',
QUES,
RESP*sum=' '*_FREQ_=' '
/ rts=6 printmiss;
this table is produced for location #703:
Location 703
-------------------------------------|
|
Response
|
|
|-------------------------------|
|
|
A
|
C
|
D
|
E
|
|----+-------+-------+-------+-------|
|Item|
|
|
|
|
|----|
|
|
|
|
|1
|
7|
14|
4|
2|
|----+-------+-------+-------+-------|
|2
|
9|
4|
9|
3|
The table for location #703 is:
Location 703
---------------------------------------------|
|
Response
|
|
|--------------------------------------|
|
|
A
|
B
|
C
|
D
|
E
|
|----+-------+-------+-------+-------+-------|
|Item|
|
|
|
|
|
|----|
|
|
|
|
|
|1
|
6|
.|
13|
4|
2|
|----+-------+-------+-------+-------+-------|
|2
|
9|
.|
4|
9|
3|
Including the PRINTMISS option in the table statement
specifies that row and column headings are to be the
same for all logical pages of the report. The TABLE
statement becomes:
The MERGE with valid responses can be used to screen
for inappropriate responses. Item 1 may have had
Table LOC='Location',
-
6 -
|
| SUM |PCTSUM| SUM |PCTSUM
|----+------+------+------+-----|Item|
|
|
|
|----|
|
|
|
|1
|
167|
2|
144|
1
|----+------+------+------+-----|2
|
157|
2|
144|
1
responses of A through D. Two people at location #703
selected the inappropriate response E. Our data step
becomes:
Data VALID;
Merge SURSUMM QUESTS (in=A);
By QUES RESP;
If _FREQ_ = . then LOC='701';
If ^A then RESP='Z';
The format=6. does not allow the display of decimal
places. This default may be overridden by adding *f=6.1
after PCTSUM:
Table QUES,
RESP*(sum pctsum*f=6.1)*
_FREQ_=' '
/ rts 6;
Any inappropriate responses have been recoded as "Z".
A format for RESP may be written which prints "Invalid"
instead of "Z".
Proc Format;
Value $rsp 'Z'='Invalid';
which gives us something a bit better:
--------------------------------|
|
|
|--------------------------|
|
A
|
B
|
|-------------+------------|
| SUM |PCTSUM| SUM |PCTSUM
|----+------+------+------+-----|Item|
|
|
|
|----|
|
|
|
|1
|
167|
1.7|
144|
1.5
|----+------+------+------+-----|2
|
157|
1.6|
144|
1.5
The resulting table becomes:
--------------------------------------Response
|
--------------------------------------|
B
|
C
|
D
|
E
|Invalid|
------+-------+-------+-------+-------|
|
|
|
|
|
|
|
|
|
|
.|
13|
4|
.|
2|
------+-------+-------+-------+-------|
.|
4|
9|
3|
.|
Decimals are displayed but the percents are much smaller
that we might anticipate.
By default, PCTSUM
calculates the percent that each sum is of all sums in the
table. The sum of all of the percents is 100%.
The two inappropriate responses are reported under the
heading "Invalid" rather than "E".
PERCENT CALCULATIONS
We would like to know what percent each sum is We
would like to know what percent each sum is of the sum
of the row. To calculate this, we must specify the
denominator definition to be used.
The TABLEstatement is:
In addition to reporting the frequency of responses, we
may be asked to include the percent responding a
particular way. Returning to our report of questions
crossed with responses, the PROC TABULATE step is:
Table QUES,
RESP*(sum pctsum<RESP>*f=6.1)*
_FREQ_=' '
/ rts 6;
Proc Tabulate format=6.;
Class QUES RESP;
Var _FREQ_;
Label QUES='Item'
RESP='Response';
Table QUES,
RESP*sum=' '*_FREQ_=' '
/ rts 6;
Our table becomes:
--------------------------------|
|
|
|--------------------------|
|
A
|
B
|
|-------------+------------|
| SUM |PCTSUM| SUM |PCTSUM
|----+------+------+------+-----|Item|
|
|
|
|----|
|
|
|
|1
|
167| 17.1|
144| 14.7
|----+------+------+------+-----|2
|
157| 16.0|
144| 14.6
We can request that percents of the sums be printed by
adding PCTSUM to the TABLE statement.
Table QUES,
RESP*(sum pctsum)*_FREQ_=' '
/ rts 6;
The resulting table is not exactly what is desired.
RESP is the denominator definition because we would
add all of the sums across all values of RESP to calculate
the percent that each value is of the total. Our percents
now sum to 100% across each row.
--------------------------------|
|
|
|--------------------------|
|
A
|
B
|
|-------------+-------------
7 -
Had we used QUES as a denominator definition, we
would have calculated the percent that a response value
was associated with each item number. The percents
would sum to 100% down each column.
*****
CONCLUSION
PROC TABULATE can best be learned by experience.
The code on the next page (attachment) will generate a
test file of survey responses.
SAS is a registered trademark in the U.S.A. of the SAS
Institute Inc., Cary NC
Use the test file to create one and two dimensional tables.
Add features to the code as you become more confident
with the Procedure. Have a clear picture of the desired
table before beginning to code.
If you have any questions or comments, you may contact
the author at:
NationsBank
10 Light Street
MD4-302-33-01
Baltimore, MD 21202
REFERENCES / ACKNOWLEDGMENTS
PROC TABULATE is covered in the manual “ SAS
Guide to TABULATE Processing “, Second Edition
(410) 605-8673 PHONE
(410) 605-1199 FAX0
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PROC TABULATE:
CONTROLLING TABLE APPEARANCE:
August V. Treff, NationsBank
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ATTACHMENT:
SAS CODE USED TO GENERATE SAMPLE DATA
Proc Format;
Value rsp
0-15 ='A'
16-30 ='B'
31-60 ='C'
61-85 ='D'
86-100='E';
Value gen
0-40 ='M'
41-100='F';
Value age
0-15 ='1'
6-70 ='2'
71-100='3';
Value grp
0-35 ='1'
36-72 ='2'
73-100='3';
Value loc
0-35 ='701'
36-71 ='702'
72-75 ='703'
76-100='704';
Data RESP;
File DISK notitles;
Do J=1 to 1000;
Do I=1 to 10;
If I=1 then do;
GENDER = put(int(100*ranuni(10)),gen.);
AGE
= put(int(100*ranuni(0)),age.);
LOC
= put(int(100*ranuni(5)),loc.);
GROUP = put(int(100*ranuni(1)),grp.);
put @1 GENDER
@2 AGE
@3 GROUP
@6 LOC @;
end;
RESP = put(int(100*ranuni(0)),rsp.);
put @I+10 RESP @;
end;
put;
end;
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