216.ANALYZING VARIETIES OF BISCUITS WORLDWIDE USING PROC SQL AND MACROS IN SAS WITH GLOBAL PRICE RATINGS FLAVOR BASED INSIGHTS AND COUNTRY WISE BRAND COMPARISON

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ANALYZING VARIETIES OF BISCUITS WORLDWIDE USING PROC SQL AND MACROS IN SAS WITH GLOBAL PRICE RATINGS FLAVOR BASED INSIGHTS AND COUNTRY WISE BRAND COMPARISON

/*Creating a unique dataset on Varieties of Biscuits Worldwide*/

/* STEP 1: Creating a Biscuit Dataset Using PROC SQL */

proc sql;

    create table Biscuits_Worldwide (

        Biscuit_ID num,

        Brand char(20),

        Country char(15),

        Flavor char(15),

        Description char(30),

        Price_Per_Kg num,

        Rating num

    );


    insert into Biscuits_Worldwide values(1, "Oreo", "USA", "Sweet", "Chocolate Cream", 10.5, 4.5);

    insert into Biscuits_Worldwide values(2, "Parle-G", "India", "Sweet", "Classic Glucose", 2.0, 4.2);

    insert into Biscuits_Worldwide values(3, "Digestive", "UK", "Semi-Sweet", "Wheat Biscuit", 6.0, 4.1);

    insert into Biscuits_Worldwide values(4, "Tim Tam", "Australia", "Sweet", "Choco Layered", 12.0, 4.6);

    insert into Biscuits_Worldwide values(5, "Marie Gold", "India", "Light-Sweet", "Tea Biscuit", 3.5, 4.0);

    insert into Biscuits_Worldwide values(6, "Bourbon", "India", "Sweet", "Chocolate Sandwich", 5.5, 4.3);

    insert into Biscuits_Worldwide values(7, "Good Day", "India", "Butter", "Cashew and Butter", 4.2, 4.1);

    insert into Biscuits_Worldwide values(8, "Nice", "India", "Coconut", "Coconut Sugar Biscuit", 4.0, 3.9);

    insert into Biscuits_Worldwide values(9, "TUC", "Belgium", "Salty", "Salted Crackers", 7.0, 4.0);

    insert into Biscuits_Worldwide values(10, "Ritz", "USA", "Salty", "Buttery Crackers", 8.0, 4.2);

    insert into Biscuits_Worldwide values(11, "Leibniz", "Germany", "Sweet", "Butter Biscuit", 9.0, 4.4);

    insert into Biscuits_Worldwide values(12, "Pally", "Netherlands", "Savory", "Cheese Herb", 6.5, 4.0);

    insert into Biscuits_Worldwide values(13, "Chips Ahoy", "USA", "Sweet", "Choco Chip Cookie", 11.0, 4.3);

    insert into Biscuits_Worldwide values(14, "Mcvities Hobnobs", "UK", "Oaty", "Oat Cookies", 7.5, 4.2);

    insert into Biscuits_Worldwide values(15, "Prince", "France", "Sweet", "Choco Filled", 9.5, 4.5);

    insert into Biscuits_Worldwide values(16, "Lotus Biscoff", "Belgium", "Caramel", "Spiced Caramelized", 10.0, 4.7);

    insert into Biscuits_Worldwide values(17, "Mcvities Jaffa", "UK", "Sweet", "Orange & Choco", 8.5, 4.1);

    insert into Biscuits_Worldwide values(18, "Cracker Jack", "USA", "Salty", "Savory Snack Biscuits", 6.0, 3.8);

quit;

proc print;run;

Output:

Obs Biscuit_ID Brand Country Flavor Description Price_Per_Kg Rating
1 1 Oreo USA Sweet Chocolate Cream 10.5 4.5
2 2 Parle-G India Sweet Classic Glucose 2.0 4.2
3 3 Digestive UK Semi-Sweet Wheat Biscuit 6.0 4.1
4 4 Tim Tam Australia Sweet Choco Layered 12.0 4.6
5 5 Marie Gold India Light-Sweet Tea Biscuit 3.5 4.0
6 6 Bourbon India Sweet Chocolate Sandwich 5.5 4.3
7 7 Good Day India Butter Cashew and Butter 4.2 4.1
8 8 Nice India Coconut Coconut Sugar Biscuit 4.0 3.9
9 9 TUC Belgium Salty Salted Crackers 7.0 4.0
10 10 Ritz USA Salty Buttery Crackers 8.0 4.2
11 11 Leibniz Germany Sweet Butter Biscuit 9.0 4.4
12 12 Pally Netherlands Savory Cheese Herb 6.5 4.0
13 13 Chips Ahoy USA Sweet Choco Chip Cookie 11.0 4.3
14 14 Mcvities Hobnobs UK Oaty Oat Cookies 7.5 4.2
15 15 Prince France Sweet Choco Filled 9.5 4.5
16 16 Lotus Biscoff Belgium Caramel Spiced Caramelized 10.0 4.7
17 17 Mcvities Jaffa UK Sweet Orange & Choco 8.5 4.1
18 18 Cracker Jack USA Salty Savory Snack Biscuits 6.0 3.8


/* STEP 2: View All Records */

proc sql;

    title "All Varieties of Biscuits Worldwide";

    select * from Biscuits_Worldwide;

quit;

Output:

All Varieties of Biscuits Worldwide

Biscuit_ID Brand Country Flavor Description Price_Per_Kg Rating
1 Oreo USA Sweet Chocolate Cream 10.5 4.5
2 Parle-G India Sweet Classic Glucose 2 4.2
3 Digestive UK Semi-Sweet Wheat Biscuit 6 4.1
4 Tim Tam Australia Sweet Choco Layered 12 4.6
5 Marie Gold India Light-Sweet Tea Biscuit 3.5 4
6 Bourbon India Sweet Chocolate Sandwich 5.5 4.3
7 Good Day India Butter Cashew and Butter 4.2 4.1
8 Nice India Coconut Coconut Sugar Biscuit 4 3.9
9 TUC Belgium Salty Salted Crackers 7 4
10 Ritz USA Salty Buttery Crackers 8 4.2
11 Leibniz Germany Sweet Butter Biscuit 9 4.4
12 Pally Netherlands Savory Cheese Herb 6.5 4
13 Chips Ahoy USA Sweet Choco Chip Cookie 11 4.3
14 Mcvities Hobnobs UK Oaty Oat Cookies 7.5 4.2
15 Prince France Sweet Choco Filled 9.5 4.5
16 Lotus Biscoff Belgium Caramel Spiced Caramelized 10 4.7
17 Mcvities Jaffa UK Sweet Orange & Choco 8.5 4.1
18 Cracker Jack USA Salty Savory Snack Biscuits 6 3.8

/* STEP 3: Summary by Country */

proc sql;

    title "Average Price and Rating of Biscuits by Country";

    select Country, count(*) as Total_Brands,

           mean(Price_Per_Kg) as Avg_Price format=8.2,

           mean(Rating) as Avg_Rating format=3.2

    from Biscuits_Worldwide

    group by Country

    order by Avg_Rating desc;

quit;

Output:

Average Price and Rating of Biscuits by Country

Country Total_Brands Avg_Price Avg_Rating
Australia 1 12.00 4.6
France 1 9.50 4.5
Germany 1 9.00 4.4
Belgium 2 8.50 4.4
USA 4 8.88 4.2
UK 3 7.33 4.1
India 5 3.84 4.1
Netherlands 1 6.50 4.0

/* STEP 4: Top 5 Expensive Biscuits */

proc sql outobs=5;

    title "Top 5 Most Expensive Biscuits in the World";

    select Brand, Country, Price_Per_Kg, Rating

    from Biscuits_Worldwide

    order by Price_Per_Kg desc;

quit;

Output:

Top 5 Most Expensive Biscuits in the World

Brand Country Price_Per_Kg Rating
Tim Tam Australia 12 4.6
Chips Ahoy USA 11 4.3
Oreo USA 10.5 4.5
Lotus Biscoff Belgium 10 4.7
Prince France 9.5 4.5

/* STEP 5: Top Rated Biscuits per Flavor */

proc sql;

    title "Top Rated Biscuits per Flavor Type";

    select Flavor, Brand, Country, max(Rating) as Top_Rating

    from Biscuits_Worldwide

    group by Flavor;

quit;

Output:

Top Rated Biscuits per Flavor Type

Flavor Brand Country Top_Rating
Butter Good Day India 4.1
Caramel Lotus Biscoff Belgium 4.7
Coconut Nice India 3.9
Light-Sweet Marie Gold India 4
Oaty Mcvities Hobnobs UK 4.2
Salty Ritz USA 4.2
Salty Cracker Jack USA 4.2
Salty TUC Belgium 4.2
Savory Pally Netherlands 4
Semi-Sweet Digestive UK 4.1
Sweet Prince France 4.6
Sweet Bourbon India 4.6
Sweet Chips Ahoy USA 4.6
Sweet Leibniz Germany 4.6
Sweet Oreo USA 4.6
Sweet Parle-G India 4.6
Sweet Tim Tam Australia 4.6
Sweet Mcvities Jaffa UK 4.6

/* STEP 6: Create Macro to Filter by Country */

%macro filter_country(cname);

    proc sql;

        title "Biscuit Varieties from &cname";

        select Brand, Flavor, Description, Price_Per_Kg, Rating

        from Biscuits_Worldwide

        where Country = "&cname"

        order by Rating desc;

    quit;

%mend;


%filter_country(India);

Output:

Biscuit Varieties from India

Brand Flavor Description Price_Per_Kg Rating
Bourbon Sweet Chocolate Sandwich 5.5 4.3
Parle-G Sweet Classic Glucose 2 4.2
Good Day Butter Cashew and Butter 4.2 4.1
Marie Gold Light-Sweet Tea Biscuit 3.5 4
Nice Coconut Coconut Sugar Biscuit 4 3.9

%filter_country(USA);

Output:

Biscuit Varieties from USA

Brand Flavor Description Price_Per_Kg Rating
Oreo Sweet Chocolate Cream 10.5 4.5
Chips Ahoy Sweet Choco Chip Cookie 11 4.3
Ritz Salty Buttery Crackers 8 4.2
Cracker Jack Salty Savory Snack Biscuits 6 3.8

/* STEP 7: Macro to Analyze by Flavor */

%macro flavor_analysis(flv);

    proc sql;

        title "Biscuit Analysis for &flv Flavor";

        select count(*) as Count, 

               avg(Price_Per_Kg) as Avg_Price format=8.2,

               avg(Rating) as Avg_Rating format=3.2

        from Biscuits_Worldwide

        where Flavor = "&flv";

    quit;

%mend;


%flavor_analysis(Sweet);

Output:

Biscuit Analysis for Sweet Flavor

Count Avg_Price Avg_Rating
8 8.50 4.4

%flavor_analysis(Salty);

Output:

Biscuit Analysis for Salty Flavor

Count Avg_Price Avg_Rating
3 7.00 4.0

%flavor_analysis(Butter);

Output:

Biscuit Analysis for Butter Flavor

Count Avg_Price Avg_Rating
1 4.20 4.1

/* STEP 8: Identify Biscuits with Rating > 4.5 */

proc sql;

    title "Highly Rated Biscuits (Rating > 4.5)";

    select Brand, Country, Flavor, Rating

    from Biscuits_Worldwide

    where Rating > 4.5;

quit;

Output:

Highly Rated Biscuits (Rating > 4.5)

Brand Country Flavor Rating
Tim Tam Australia Sweet 4.6
Lotus Biscoff Belgium Caramel 4.7

/* STEP 9: Country-wise Flavor Distribution */

proc sql;

    title "Number of Biscuit Flavors per Country";

    select Country, Flavor, count(*) as Count

    from Biscuits_Worldwide

    group by Country, Flavor

    order by Country, Count desc;

quit;

Output:

Number of Biscuit Flavors per Country

Country Flavor Count
Australia Sweet 1
Belgium Salty 1
Belgium Caramel 1
France Sweet 1
Germany Sweet 1
India Sweet 2
India Coconut 1
India Butter 1
India Light-Sweet 1
Netherlands Savory 1
UK Sweet 1
UK Semi-Sweet 1
UK Oaty 1
USA Sweet 2
USA Salty 2

/* STEP 10: Macro to Rank Biscuits in Each Country by Price */

%macro rank_biscuits_by_price;

    proc sql;

        title "Top Biscuit Brands by Price in Each Country";

        create table Top_Priced_Biscuits as

        select a.Country, a.Brand, a.Price_Per_Kg

        from Biscuits_Worldwide as a

        inner join (

            select Country, max(Price_Per_Kg) as Max_Price

            from Biscuits_Worldwide

            group by Country

        ) as b

        on a.Country = b.Country and a.Price_Per_Kg = b.Max_Price;


        select * from Top_Priced_Biscuits;

    quit;

%mend;


%rank_biscuits_by_price;

Output:
Top Biscuit Brands by Price in Each Country

Country Brand Price_Per_Kg
Australia Tim Tam 12
India Bourbon 5.5
Germany Leibniz 9
Netherlands Pally 6.5
USA Chips Ahoy 11
France Prince 9.5
Belgium Lotus Biscoff 10
UK Mcvities Jaffa 8.5


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