Chapter 15 : Creating Customized Reports
Although you can
customize the output produced by PROC PRINT, there are times when you need a
bit more control over the appearance of your report. PROC REPORT was developed
to fit this need. Not only can you control the appearance of every column of your
report, you can produce summary reports as well as detail listings.
Code: ch15_6.sas
/*6.Using
the SAS data set Blood Pressure, produce a report showing Gender, Age, SBP,
and DBP.
Order the report in Gender and Age order as shown here:
Subject's
in Gender and Age Order
Systolic
Diastolic
Blood
Blood
Gender Age
Pressure Pressure
F 28 120
70
48 138 88
68 110 62
78 132 76
M 23 144
90
35 142 82
45 150 96
55 130
80*/
title "Subject's in
Gender and Age Order";
proc report data=a15022.bloodpressure
nowd;
column Gender Age SBP DBP;
define Gender / order width=6;
define Age / order width=5;
define SBP / display "Systolic Blood
Pressure"
width=8;
define DBP / display "Diastolic Blood
Pressure"
width=9;
run;
Learning:
Program defines format for each column such as age, blood pressure.
It outputs a report which is easy and nice to read and understand.
Output:
Subject's in Gender and Age Order
Gender
|
Age
|
Systolic Blood
Pressure
|
Diastolic Blood
Pressure
|
F
|
28
|
120
|
70
|
|
48
|
138
|
88
|
|
68
|
110
|
62
|
|
78
|
132
|
76
|
M
|
23
|
144
|
90
|
|
35
|
142
|
82
|
|
45
|
150
|
96
|
|
55
|
130
|
80
|
Code:
ch15_8.sas
data a15022.blood;
infile '/folders/myfolders/programs/blood.txt' truncover;
length Gender $ 6 BloodType $ 2 AgeGroup $ 5;
input Subject
Gender
BloodType
AgeGroup
WBC
RBC
Chol;
label Gender = "Gender"
BloodType = "Blood Type"
AgeGroup = "Age Group"
Chol = "Cholesterol";
run;
title "Average Blood Counts by Gender";
proc report data=a15022.blood nowd headline;
column BloodType Gender,WBC Gender,RBC;
define BloodType / group 'Blood Type' width=5;
define Gender / across width=8 '-Gender-';
define WBC / analysis mean format=comma8.;
define RBC / analysis mean format=8.2;
run;
Learning:
We could aggregate data by gender and then by blood type
using above code.
Output:
Average Blood Counts by Gender
|
Gender
|
Gender
|
|
Female
|
Male
|
Female
|
Male
|
Blood Type
|
WBC
|
WBC
|
RBC
|
RBC
|
A
|
7,218
|
7,051
|
5.47
|
5.46
|
AB
|
7,421
|
6,893
|
5.43
|
5.69
|
B
|
6,716
|
6,991
|
5.52
|
5.42
|
O
|
7,050
|
6,930
|
5.53
|
5.48
|
Chapter 16: Summarizing
your data
You may have
thought of PROC MEANS (or PROC SUMMARY) primarily as a way to
generate summary reports, reporting the sums and means of your numeric
variables.
However, these procedures are much more versatile and can be used to create
summary
data sets that can then be analyzed with more DATA or PROC steps.
All the examples in this chapter use PROC MEANS rather than PROC SUMMARY,
even when all you want is an output data set. The reason for this is that using
PROC
MEANS with a NOPRINT option is identical to using PROC SUMMARY.
Code: Ch16_4.sas
proc format library=a15022;
value $yesno 'Y','1' = 'Yes'
'N','0' = 'No'
' ' = 'Not Given';
value $size 'S' = 'Small'
'M' = 'Medium'
'L' = 'Large'
' ' = 'Missing';
value $gender 'F' = 'Female'
'M' = 'Male'
' ' = 'Not Given';
run;
data a15022.college;
length StudentID $ 5 Gender SchoolSize $ 1;
do i = 1 to 100;
StudentID = put(round(ranuni(123456)*10000),z5.);
if ranuni(0) lt .4 then Gender = 'M';
else Gender = 'F';
if ranuni(0) lt .3 then SchoolSize = 'S';
else if ranuni(0) lt .7 then SchoolSize = 'M';
else SchoolSize = 'L';
if ranuni(0) lt .2 then Scholarship = 'Y';
else Scholarship = 'N';
GPA = round(rannor(0)*.5 + 3.5,.01);
if GPA gt 4 then GPA = 4;
ClassRank = int(ranuni(0)*60 + 41);
if ranuni(0) lt .1 then call missing(ClassRank);
if ranuni(0) lt .05 then call missing(SchoolSize);
if ranuni(0) lt .05 then call missing(GPA);
output;
end;
format Gender $gender1.
SchoolSize $size.
Scholarship $yesno.;
drop i;
run;
proc format;
value $groupsize
'S','M' = 'Small and Medium'
'L' = 'Large';
run;
title "Statistics on the College Data Set";
title2 "Broken down by School Size";
proc means data=a15022.college
n mean median min max maxdec=2;
class SchoolSize;
var ClassRank GPA;
format SchoolSize $groupsize.;
run;
Learning:
Usage of proc means to generate more detail report and
finding specific statistic like min, max, median.
Output:
Statistics on the
College Data Set
Broken down by School Size
The MEANS Procedure
SchoolSize
|
N Obs
|
Variable
|
N
|
Mean
|
Median
|
Minimum
|
Maximum
|
Large
|
18
|
ClassRank
GPA
|
15
16
|
72.80
3.61
|
71.00
3.61
|
45.00
2.98
|
98.00
4.00
|
Small and Medium
|
78
|
ClassRank
GPA
|
69
75
|
71.83
3.47
|
73.00
3.62
|
41.00
2.29
|
100.00
4.00
|
Code:
Ch16_5.sas
proc format;
value rank 0-50 = 'Bottom Half'
51-74 = 'Third Quartile'
75-100 = 'Top Quarter';
run;
title "Statistics on the College Data Set";
title2 "Broken down by School Size";
proc means data=a15022.college
n mean maxdec=2;
class ClassRank;
var GPA;
format ClassRank rank.;
run;
Learning:
In above program we are diving students in quartiles
according to their marks.
Output:
Statistics on the
College Data Set
Broken down by School Size
The MEANS Procedure
Analysis Variable :
GPA
|
ClassRank
|
N Obs
|
N
|
Mean
|
Bottom Half
|
15
|
14
|
3.78
|
Third Quartile
|
34
|
34
|
3.52
|
Top Quarter
|
39
|
35
|
3.42
|
Chapter 7: Counting
frequencies
PROC FREQ can be
used to count frequencies of both character and numeric variables, in one-way,
two-way, and three-way tables. In addition, you can use PROC FREQ to create
output data sets containing counts and percentages. Finally, if you are
statistically inclined, you can use this procedure to compute various statistics
such as chi-square, odds ratio, and relative risk.
Code: Ch17_1.sas
title "One-way Frequencies from BLOOD Data Set";
proc freq data=a15022.blood;
tables Gender BloodType AgeGroup / nocum nopercent;
run;
Learning:
In above program we learn
usage of proc freq and tables statement to count and display one way
frequencies.
Output:
One-way Frequencies from BLOOD Data Set
The FREQ Procedure
Gender
|
Gender
|
Frequency
|
Female
|
440
|
Male
|
560
|
Blood Type
|
BloodType
|
Frequency
|
A
|
412
|
AB
|
44
|
B
|
96
|
O
|
448
|
Age Group
|
AgeGroup
|
Frequency
|
Old
|
598
|
Young
|
402
|
Code: Ch17_2.sas
proc format;
value agegrp low-40 = '40 and lower'
41-60 = '41 to 60'
61-high = '61 and higher';
run;
title "Using a Format to Regroup Values";
proc freq data=a15022.bloodpressure;
tables age / nocum nopercent;
format age agegrp.;
run;
Learning:
Above
program shows frequency as per age group using tables statement.
Output:
Using a Format to Regroup Values
The FREQ Procedure
Age
|
Frequency
|
40 and lower
|
3
|
41 to 60
|
3
|
61 and higher
|
2
|
Please click on below link
to find all the programs…
