264.TEMPLES OF INDIA DATASET ANALYSIS USING PROC PRINT | PROC CONTENTS | PROC SORT | PROC FREQ | PROC MEANS | PROC SQL | PROC TABULATE | PROC REPORT | PROC TRANSPOSE | PROC FORMAT | PROC RANK | PROC SGPLOT | MACROS

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242.COMPREHENSIVE HOME TOUR DATASET ANALYSIS OF 3 DIFFERENT FAMILIES USING PROC PRINT | PROC SORT | PROC MEANS | PROC SQL | PROC FREQ | PROC FORMAT | MACROS IN SAS

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COMPREHENSIVE HOME TOUR DATASET ANALYSIS OF 3 DIFFERENT FAMILIES USING PROC PRINT |  PROC SORT | PROC MEANS | PROC SQL | PROC FREQ | PROC FORMAT | MACROS IN SAS

/*Creating A Home Tour Dataset of 3 Different Families*/

1.CREATING THE DATASET

options nocenter;

data Home_Tour;

    length Family_ID $2 Family_Name $15 Room_ID $5 Room_Type $15 Flooring_Type $10 

           AC_Available $3 Room_Color $10;

    input Family_ID $ Family_Name $ Room_ID $ Room_Type $ Floor Area_SqFt Cost 

          Flooring_Type $ AC_Available $ Room_Color $;

    datalines;

F1 Sharma R001 Bedroom 1 180 120000 Tile Yes Blue

F1 Sharma R002 Kitchen 1 140 80000 Marble No White

F1 Sharma R003 LivingRoom 1 250 150000 Tile Yes Cream

F1 Sharma R004 Bathroom 1 100 50000 Tile No White

F1 Sharma R005 Balcony 1 90 30000 Tile No Green

F1 Sharma R006 Bedroom 2 190 125000 Wood Yes Yellow

F2 Fernandez R007 Bedroom 1 200 130000 Wood Yes Blue

F2 Fernandez R008 Kitchen 1 160 85000 Marble Yes Yellow

F2 Fernandez R009 LivingRoom 1 260 155000 Marble Yes Grey

F2 Fernandez R010 Bathroom 1 110 60000 Tile No White

F2 Fernandez R011 Balcony 1 95 32000 Tile No Brown

F2 Fernandez R012 Study 2 150 110000 Tile Yes White

F2 Fernandez R013 Bedroom 2 195 128000 Wood Yes Blue

F3 Patil R014 Bedroom 1 185 122000 Tile Yes Green

F3 Patil R015 Kitchen 1 145 78000 Marble No White

F3 Patil R016 LivingRoom 1 245 149000 Wood Yes Grey

F3 Patil R017 Bathroom 1 105 54000 Tile No Yellow

F3 Patil R018 StoreRoom 1 90 40000 Tile No Cream

F3 Patil R019 Bedroom 2 180 120000 Marble Yes Blue

F3 Patil R020 Bedroom 3 175 119000 Wood Yes Yellow

F3 Patil R021 Balcony 2 100 35000 Tile No Green

F3 Patil R022 Study 2 160 115000 Wood Yes White

F3 Patil R023 PujaRoom 2 85 45000 Marble Yes Red

F3 Patil R024 Gym 2 200 140000 Wood Yes Grey

F3 Patil R025 Terrace 3 300 175000 Tile No White

;

run;

proc print;run;

Output:

Obs Family_ID Family_Name Room_ID Room_Type Flooring_Type AC_Available Room_Color Floor Area_SqFt Cost
1 F1 Sharma R001 Bedroom Tile Yes Blue 1 180 120000
2 F1 Sharma R002 Kitchen Marble No White 1 140 80000
3 F1 Sharma R003 LivingRoom Tile Yes Cream 1 250 150000
4 F1 Sharma R004 Bathroom Tile No White 1 100 50000
5 F1 Sharma R005 Balcony Tile No Green 1 90 30000
6 F1 Sharma R006 Bedroom Wood Yes Yellow 2 190 125000
7 F2 Fernandez R007 Bedroom Wood Yes Blue 1 200 130000
8 F2 Fernandez R008 Kitchen Marble Yes Yellow 1 160 85000
9 F2 Fernandez R009 LivingRoom Marble Yes Grey 1 260 155000
10 F2 Fernandez R010 Bathroom Tile No White 1 110 60000
11 F2 Fernandez R011 Balcony Tile No Brown 1 95 32000
12 F2 Fernandez R012 Study Tile Yes White 2 150 110000
13 F2 Fernandez R013 Bedroom Wood Yes Blue 2 195 128000
14 F3 Patil R014 Bedroom Tile Yes Green 1 185 122000
15 F3 Patil R015 Kitchen Marble No White 1 145 78000
16 F3 Patil R016 LivingRoom Wood Yes Grey 1 245 149000
17 F3 Patil R017 Bathroom Tile No Yellow 1 105 54000
18 F3 Patil R018 StoreRoom Tile No Cream 1 90 40000
19 F3 Patil R019 Bedroom Marble Yes Blue 2 180 120000
20 F3 Patil R020 Bedroom Wood Yes Yellow 3 175 119000
21 F3 Patil R021 Balcony Tile No Green 2 100 35000
22 F3 Patil R022 Study Wood Yes White 2 160 115000
23 F3 Patil R023 PujaRoom Marble Yes Red 2 85 45000
24 F3 Patil R024 Gym Wood Yes Grey 2 200 140000
25 F3 Patil R025 Terrace Tile No White 3 300 175000


2.PROC PRINT – RAW VIEW

proc print data=Home_Tour noobs;

    title "Full Home Tour Dataset of All Families";

run;

Output:

Full Home Tour Dataset of All Families

Family_ID Family_Name Room_ID Room_Type Flooring_Type AC_Available Room_Color Floor Area_SqFt Cost
F1 Sharma R001 Bedroom Tile Yes Blue 1 180 120000
F1 Sharma R002 Kitchen Marble No White 1 140 80000
F1 Sharma R003 LivingRoom Tile Yes Cream 1 250 150000
F1 Sharma R004 Bathroom Tile No White 1 100 50000
F1 Sharma R005 Balcony Tile No Green 1 90 30000
F1 Sharma R006 Bedroom Wood Yes Yellow 2 190 125000
F2 Fernandez R007 Bedroom Wood Yes Blue 1 200 130000
F2 Fernandez R008 Kitchen Marble Yes Yellow 1 160 85000
F2 Fernandez R009 LivingRoom Marble Yes Grey 1 260 155000
F2 Fernandez R010 Bathroom Tile No White 1 110 60000
F2 Fernandez R011 Balcony Tile No Brown 1 95 32000
F2 Fernandez R012 Study Tile Yes White 2 150 110000
F2 Fernandez R013 Bedroom Wood Yes Blue 2 195 128000
F3 Patil R014 Bedroom Tile Yes Green 1 185 122000
F3 Patil R015 Kitchen Marble No White 1 145 78000
F3 Patil R016 LivingRoom Wood Yes Grey 1 245 149000
F3 Patil R017 Bathroom Tile No Yellow 1 105 54000
F3 Patil R018 StoreRoom Tile No Cream 1 90 40000
F3 Patil R019 Bedroom Marble Yes Blue 2 180 120000
F3 Patil R020 Bedroom Wood Yes Yellow 3 175 119000
F3 Patil R021 Balcony Tile No Green 2 100 35000
F3 Patil R022 Study Wood Yes White 2 160 115000
F3 Patil R023 PujaRoom Marble Yes Red 2 85 45000
F3 Patil R024 Gym Wood Yes Grey 2 200 140000
F3 Patil R025 Terrace Tile No White 3 300 175000


3.PROC SORT – BY FAMILY AND ROOM TYPE

proc sort data=Home_Tour out=Sorted_Home;

    by Family_Name Room_Type;

run;


proc print data=Sorted_Home;

    title "Sorted Home Tour Data by Family and Room Type";

run;

Output:

Sorted Home Tour Data by Family and Room Type

Obs Family_ID Family_Name Room_ID Room_Type Flooring_Type AC_Available Room_Color Floor Area_SqFt Cost
1 F2 Fernandez R011 Balcony Tile No Brown 1 95 32000
2 F2 Fernandez R010 Bathroom Tile No White 1 110 60000
3 F2 Fernandez R007 Bedroom Wood Yes Blue 1 200 130000
4 F2 Fernandez R013 Bedroom Wood Yes Blue 2 195 128000
5 F2 Fernandez R008 Kitchen Marble Yes Yellow 1 160 85000
6 F2 Fernandez R009 LivingRoom Marble Yes Grey 1 260 155000
7 F2 Fernandez R012 Study Tile Yes White 2 150 110000
8 F3 Patil R021 Balcony Tile No Green 2 100 35000
9 F3 Patil R017 Bathroom Tile No Yellow 1 105 54000
10 F3 Patil R014 Bedroom Tile Yes Green 1 185 122000
11 F3 Patil R019 Bedroom Marble Yes Blue 2 180 120000
12 F3 Patil R020 Bedroom Wood Yes Yellow 3 175 119000
13 F3 Patil R024 Gym Wood Yes Grey 2 200 140000
14 F3 Patil R015 Kitchen Marble No White 1 145 78000
15 F3 Patil R016 LivingRoom Wood Yes Grey 1 245 149000
16 F3 Patil R023 PujaRoom Marble Yes Red 2 85 45000
17 F3 Patil R018 StoreRoom Tile No Cream 1 90 40000
18 F3 Patil R022 Study Wood Yes White 2 160 115000
19 F3 Patil R025 Terrace Tile No White 3 300 175000
20 F1 Sharma R005 Balcony Tile No Green 1 90 30000
21 F1 Sharma R004 Bathroom Tile No White 1 100 50000
22 F1 Sharma R001 Bedroom Tile Yes Blue 1 180 120000
23 F1 Sharma R006 Bedroom Wood Yes Yellow 2 190 125000
24 F1 Sharma R002 Kitchen Marble No White 1 140 80000
25 F1 Sharma R003 LivingRoom Tile Yes Cream 1 250 150000


4.PROC MEANS – AVERAGE ROOM SIZE AND COST

proc means data=Home_Tour mean max min sum;

    class Family_Name;

    var Area_SqFt Cost;

    title "Summary Statistics: Area and Cost by Family";

run;

Output:

Summary Statistics: Area and Cost by Family

The MEANS Procedure

Family_Name N Obs Variable Mean Maximum Minimum Sum
Fernandez 7
Area_SqFt
Cost
167.1428571
100000.00
260.0000000
155000.00
95.0000000
32000.00
1170.00
700000.00
Patil 12
Area_SqFt
Cost
164.1666667
99333.33
300.0000000
175000.00
85.0000000
35000.00
1970.00
1192000.00
Sharma 6
Area_SqFt
Cost
158.3333333
92500.00
250.0000000
150000.00
90.0000000
30000.00
950.0000000
555000.00


5.PROC FREQ – FLOORING TYPE DISTRIBUTION

proc freq data=Home_Tour;

    tables Flooring_Type*Family_Name / nocum nopercent;

    title "Flooring Type Distribution per Family";

run;

Output:

Flooring Type Distribution per Family

The FREQ Procedure

Frequency
Row Pct
Col Pct
Table of Flooring_Type by Family_Name
Flooring_Type Family_Name
Fernandez Patil Sharma Total
Marble
2
33.33
28.57
3
50.00
25.00
1
16.67
16.67
6
 
 
Tile
3
25.00
42.86
5
41.67
41.67
4
33.33
66.67
12
 
 
Wood
2
28.57
28.57
4
57.14
33.33
1
14.29
16.67
7
 
 
Total
7
12
6
25


6.PROC SQL – COMPLEX ANALYTICS

a.Get Most Expensive Room per Family

proc sql;

    create table Most_Expensive as

    select Family_Name, Room_Type, max(Cost) as Max_Cost

    from Home_Tour

    group by Family_Name;

quit;


proc print data=Most_Expensive;

    title "Most Expensive Room by Each Family";

run;

Output:

Most Expensive Room by Each Family

Obs Family_Name Room_Type Max_Cost
1 Fernandez Balcony 155000
2 Fernandez Bedroom 155000
3 Fernandez Bathroom 155000
4 Fernandez Study 155000
5 Fernandez Bedroom 155000
6 Fernandez LivingRoom 155000
7 Fernandez Kitchen 155000
8 Patil Bedroom 175000
9 Patil Gym 175000
10 Patil Study 175000
11 Patil Kitchen 175000
12 Patil Balcony 175000
13 Patil Bedroom 175000
14 Patil StoreRoom 175000
15 Patil Bedroom 175000
16 Patil PujaRoom 175000
17 Patil Terrace 175000
18 Patil Bathroom 175000
19 Patil LivingRoom 175000
20 Sharma LivingRoom 150000
21 Sharma Bedroom 150000
22 Sharma Balcony 150000
23 Sharma Bedroom 150000
24 Sharma Kitchen 150000
25 Sharma Bathroom 150000


b.Total Room Cost per Family

proc sql;

    select Family_Name, sum(Cost) as Total_Cost

    from Home_Tour

    group by Family_Name;

quit;

Output:

Family_Name Total_Cost
Fernandez 700000
Patil 1192000
Sharma 555000


c.Rooms with Area > 200 SqFt

proc sql;

    select * from Home_Tour

    where Area_SqFt > 200;

quit;

Output:

Family_ID Family_Name Room_ID Room_Type Flooring_Type AC_Available Room_Color Floor Area_SqFt Cost
F1 Sharma R003 LivingRoom Tile Yes Cream 1 250 150000
F2 Fernandez R009 LivingRoom Marble Yes Grey 1 260 155000
F3 Patil R016 LivingRoom Wood Yes Grey 1 245 149000
F3 Patil R025 Terrace Tile No White 3 300 175000


7.FORMATTING OUTPUTS – PROC FORMAT

proc format;

    value $floorfmt 'Yes' = 'With AC'

                    'No' = 'No AC';

    value costfmt low-<80000 = 'Low'

                  80000-<130000 = 'Medium'

                  130000-high = 'High';

run;


proc print data=Home_Tour;

    format AC_Available $floorfmt. Cost costfmt.;

    title "Formatted Home Tour with Cost Ranges and AC Info";

run;

Output:

Formatted Home Tour with Cost Ranges and AC Info

Obs Family_ID Family_Name Room_ID Room_Type Flooring_Type AC_Available Room_Color Floor Area_SqFt Cost
1 F1 Sharma R001 Bedroom Tile With AC Blue 1 180 Medium
2 F1 Sharma R002 Kitchen Marble No AC White 1 140 Medium
3 F1 Sharma R003 LivingRoom Tile With AC Cream 1 250 High
4 F1 Sharma R004 Bathroom Tile No AC White 1 100 Low
5 F1 Sharma R005 Balcony Tile No AC Green 1 90 Low
6 F1 Sharma R006 Bedroom Wood With AC Yellow 2 190 Medium
7 F2 Fernandez R007 Bedroom Wood With AC Blue 1 200 High
8 F2 Fernandez R008 Kitchen Marble With AC Yellow 1 160 Medium
9 F2 Fernandez R009 LivingRoom Marble With AC Grey 1 260 High
10 F2 Fernandez R010 Bathroom Tile No AC White 1 110 Low
11 F2 Fernandez R011 Balcony Tile No AC Brown 1 95 Low
12 F2 Fernandez R012 Study Tile With AC White 2 150 Medium
13 F2 Fernandez R013 Bedroom Wood With AC Blue 2 195 Medium
14 F3 Patil R014 Bedroom Tile With AC Green 1 185 Medium
15 F3 Patil R015 Kitchen Marble No AC White 1 145 Low
16 F3 Patil R016 LivingRoom Wood With AC Grey 1 245 High
17 F3 Patil R017 Bathroom Tile No AC Yellow 1 105 Low
18 F3 Patil R018 StoreRoom Tile No AC Cream 1 90 Low
19 F3 Patil R019 Bedroom Marble With AC Blue 2 180 Medium
20 F3 Patil R020 Bedroom Wood With AC Yellow 3 175 Medium
21 F3 Patil R021 Balcony Tile No AC Green 2 100 Low
22 F3 Patil R022 Study Wood With AC White 2 160 Medium
23 F3 Patil R023 PujaRoom Marble With AC Red 2 85 Low
24 F3 Patil R024 Gym Wood With AC Grey 2 200 High
25 F3 Patil R025 Terrace Tile No AC White 3 300 High


8.MACRO – AUTOMATED FAMILY REPORTING

%macro family_report(fam);

    title "Room Report for Family: &fam.";

    proc print data=Home_Tour;

        where Family_Name="&fam.";

    run;


    proc means data=Home_Tour;

        where Family_Name="&fam.";

        var Area_SqFt Cost;

    run;


    proc freq data=Home_Tour;

        where Family_Name="&fam.";

        tables Room_Type;

    run;

%mend;


%family_report(Sharma)

Output:

Room Report for Family: Sharma

Obs Family_ID Family_Name Room_ID Room_Type Flooring_Type AC_Available Room_Color Floor Area_SqFt Cost
1 F1 Sharma R001 Bedroom Tile Yes Blue 1 180 120000
2 F1 Sharma R002 Kitchen Marble No White 1 140 80000
3 F1 Sharma R003 LivingRoom Tile Yes Cream 1 250 150000
4 F1 Sharma R004 Bathroom Tile No White 1 100 50000
5 F1 Sharma R005 Balcony Tile No Green 1 90 30000
6 F1 Sharma R006 Bedroom Wood Yes Yellow 2 190 125000

Room Report for Family: Sharma

The MEANS Procedure

Variable N Mean Std Dev Minimum Maximum
Area_SqFt
Cost
6
6
158.3333333
92500.00
60.4703784
46877.50
90.0000000
30000.00
250.0000000
150000.00

Room Report for Family: Sharma

The FREQ Procedure

Room_Type Frequency Percent Cumulative
Frequency		 Cumulative
Percent
Balcony 1 16.67 1 16.67
Bathroom 1 16.67 2 33.33
Bedroom 2 33.33 4 66.67
Kitchen 1 16.67 5 83.33
LivingRoom 1 16.67 6 100.00

%family_report(Fernandez)

Output:

Room Report for Family: Fernandez

Obs Family_ID Family_Name Room_ID Room_Type Flooring_Type AC_Available Room_Color Floor Area_SqFt Cost
7 F2 Fernandez R007 Bedroom Wood Yes Blue 1 200 130000
8 F2 Fernandez R008 Kitchen Marble Yes Yellow 1 160 85000
9 F2 Fernandez R009 LivingRoom Marble Yes Grey 1 260 155000
10 F2 Fernandez R010 Bathroom Tile No White 1 110 60000
11 F2 Fernandez R011 Balcony Tile No Brown 1 95 32000
12 F2 Fernandez R012 Study Tile Yes White 2 150 110000
13 F2 Fernandez R013 Bedroom Wood Yes Blue 2 195 128000

Room Report for Family: Fernandez

The MEANS Procedure

Variable N Mean Std Dev Minimum Maximum
Area_SqFt
Cost
7
7
167.1428571
100000.00
56.7051690
43316.66
95.0000000
32000.00
260.0000000
155000.00

Room Report for Family: Fernandez

The FREQ Procedure

Room_Type Frequency Percent Cumulative
Frequency		 Cumulative
Percent
Balcony 1 14.29 1 14.29
Bathroom 1 14.29 2 28.57
Bedroom 2 28.57 4 57.14
Kitchen 1 14.29 5 71.43
LivingRoom 1 14.29 6 85.71
Study 1 14.29 7 100.00

%family_report(Patil)

Output:

Room Report for Family: Patil

Obs Family_ID Family_Name Room_ID Room_Type Flooring_Type AC_Available Room_Color Floor Area_SqFt Cost
14 F3 Patil R014 Bedroom Tile Yes Green 1 185 122000
15 F3 Patil R015 Kitchen Marble No White 1 145 78000
16 F3 Patil R016 LivingRoom Wood Yes Grey 1 245 149000
17 F3 Patil R017 Bathroom Tile No Yellow 1 105 54000
18 F3 Patil R018 StoreRoom Tile No Cream 1 90 40000
19 F3 Patil R019 Bedroom Marble Yes Blue 2 180 120000
20 F3 Patil R020 Bedroom Wood Yes Yellow 3 175 119000
21 F3 Patil R021 Balcony Tile No Green 2 100 35000
22 F3 Patil R022 Study Wood Yes White 2 160 115000
23 F3 Patil R023 PujaRoom Marble Yes Red 2 85 45000
24 F3 Patil R024 Gym Wood Yes Grey 2 200 140000
25 F3 Patil R025 Terrace Tile No White 3 300 175000

Room Report for Family: Patil

The MEANS Procedure

Variable N Mean Std Dev Minimum Maximum
Area_SqFt
Cost
12
12
164.1666667
99333.33
65.2559065
47233.14
85.0000000
35000.00
300.0000000
175000.00

Room Report for Family: Patil

The FREQ Procedure

Room_Type Frequency Percent Cumulative
Frequency		 Cumulative
Percent
Balcony 1 8.33 1 8.33
Bathroom 1 8.33 2 16.67
Bedroom 3 25.00 5 41.67
Gym 1 8.33 6 50.00
Kitchen 1 8.33 7 58.33
LivingRoom 1 8.33 8 66.67
PujaRoom 1 8.33 9 75.00
StoreRoom 1 8.33 10 83.33
Study 1 8.33 11 91.67
Terrace 1 8.33 12 100.00

9.ADDITIONAL ANALYSIS

a.Room Count by Type

proc sql;

    select Room_Type, count(*) as Count

    from Home_Tour

    group by Room_Type;

quit;

Output:

Room_Type Count
Balcony 3
Bathroom 3
Bedroom 7
Gym 1
Kitchen 3
LivingRoom 3
PujaRoom 1
StoreRoom 1
Study 2
Terrace 1


b.Top 5 Most Expensive Rooms

proc sql outobs=5;

    select * from Home_Tour

    order by Cost desc;

quit;

Output:

Family_ID Family_Name Room_ID Room_Type Flooring_Type AC_Available Room_Color Floor Area_SqFt Cost
F3 Patil R025 Terrace Tile No White 3 300 175000
F2 Fernandez R009 LivingRoom Marble Yes Grey 1 260 155000
F1 Sharma R003 LivingRoom Tile Yes Cream 1 250 150000
F3 Patil R016 LivingRoom Wood Yes Grey 1 245 149000
F3 Patil R024 Gym Wood Yes Grey 2 200 140000


10.USING CONDITIONAL STATEMENTS

a.Flag expensive rooms:

data Home_Tour_Flagged;

    set Home_Tour;

    if Cost > 130000 then Expensive = "Yes";

    else Expensive = "No";

run;

proc print;run;

Output:

Obs Family_ID Family_Name Room_ID Room_Type Flooring_Type AC_Available Room_Color Floor Area_SqFt Cost Expensive
1 F1 Sharma R001 Bedroom Tile Yes Blue 1 180 120000 No
2 F1 Sharma R002 Kitchen Marble No White 1 140 80000 No
3 F1 Sharma R003 LivingRoom Tile Yes Cream 1 250 150000 Yes
4 F1 Sharma R004 Bathroom Tile No White 1 100 50000 No
5 F1 Sharma R005 Balcony Tile No Green 1 90 30000 No
6 F1 Sharma R006 Bedroom Wood Yes Yellow 2 190 125000 No
7 F2 Fernandez R007 Bedroom Wood Yes Blue 1 200 130000 No
8 F2 Fernandez R008 Kitchen Marble Yes Yellow 1 160 85000 No
9 F2 Fernandez R009 LivingRoom Marble Yes Grey 1 260 155000 Yes
10 F2 Fernandez R010 Bathroom Tile No White 1 110 60000 No
11 F2 Fernandez R011 Balcony Tile No Brown 1 95 32000 No
12 F2 Fernandez R012 Study Tile Yes White 2 150 110000 No
13 F2 Fernandez R013 Bedroom Wood Yes Blue 2 195 128000 No
14 F3 Patil R014 Bedroom Tile Yes Green 1 185 122000 No
15 F3 Patil R015 Kitchen Marble No White 1 145 78000 No
16 F3 Patil R016 LivingRoom Wood Yes Grey 1 245 149000 Yes
17 F3 Patil R017 Bathroom Tile No Yellow 1 105 54000 No
18 F3 Patil R018 StoreRoom Tile No Cream 1 90 40000 No
19 F3 Patil R019 Bedroom Marble Yes Blue 2 180 120000 No
20 F3 Patil R020 Bedroom Wood Yes Yellow 3 175 119000 No
21 F3 Patil R021 Balcony Tile No Green 2 100 35000 No
22 F3 Patil R022 Study Wood Yes White 2 160 115000 No
23 F3 Patil R023 PujaRoom Marble Yes Red 2 85 45000 No
24 F3 Patil R024 Gym Wood Yes Grey 2 200 140000 Yes
25 F3 Patil R025 Terrace Tile No White 3 300 175000 Yes


proc freq data=Home_Tour_Flagged;

    tables Expensive;

    title "Frequency of Expensive Rooms (>1.3 Lakh)";

run;

Output:
Frequency of Expensive Rooms (>1.3 Lakh)

The FREQ Procedure

Expensive Frequency Percent Cumulative
Frequency		 Cumulative
Percent
No 20 80.00 20 80.00
Yes 5 20.00 25 100.00






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