350.GAMING PLAYERS PERFORMANCE ANALYSIS USING SAS DATA STEP | PROC SQL | PROC MEANS | PROC UNIVARIATE | PROC SGPLOT | MACROS | DATE FUNCTIONS | APPEND | MERGE | TRANSPOSE

GAMING PLAYERS PERFORMANCE ANALYSIS USING SAS DATA STEP | PROC SQL | PROC MEANS | PROC UNIVARIATE | PROC SGPLOT | MACROS | DATE FUNCTIONS | APPEND | MERGE | TRANSPOSE

options nocenter;

1.GAMING PLAYERS DATASET CREATION

data work.gaming_players;

    length Player_Name $20 Country $15;

    format Join_Date Last_Play_Date date9.;

    input Player_Name $ Country $ Hours_Played Wins Kills Rank Join_Date :date9.;

          Last_Play_Date = intnx('day', Join_Date, ceil(Hours_Played/10));

    datalines;

Alex    USA     520  120  3400  1 01JAN2024

Ravi    India   480  110  3100  2 15JAN2024

Chen    China   460  105  2950  3 01FEB2024

Carlos  Brazil  430  98   2700  4 10FEB2024

Ivan    Russia  410  95   2600  5 20FEB2024

Leo     France  390  90   2450  6 01MAR2024

Sam     UK      360  85   2300  7 10MAR2024

Noah    Canada  340  80   2150  8 15MAR2024

Ali     UAE     320  75   2000  9 20MAR2024

Tom     Australia 300 70  1850 10 01APR2024

Ken     Japan   280  65   1700 11 05APR2024

Mark    Germany 260  60   1550 12 10APR2024

;

run;

proc print data=work.gaming_players;

run;

OUTPUT:

Obs	Player_Name	Country	Join_Date	Last_Play_Date	Hours_Played	Wins	Kills	Rank
1	Alex	USA	01JAN2024	22FEB2024	520	120	3400	1
2	Ravi	India	15JAN2024	03MAR2024	480	110	3100	2
3	Chen	China	01FEB2024	18MAR2024	460	105	2950	3
4	Carlos	Brazil	10FEB2024	24MAR2024	430	98	2700	4
5	Ivan	Russia	20FEB2024	01APR2024	410	95	2600	5
6	Leo	France	01MAR2024	09APR2024	390	90	2450	6
7	Sam	UK	10MAR2024	15APR2024	360	85	2300	7
8	Noah	Canada	15MAR2024	18APR2024	340	80	2150	8
9	Ali	UAE	20MAR2024	21APR2024	320	75	2000	9
10	Tom	Australia	01APR2024	01MAY2024	300	70	1850	10
11	Ken	Japan	05APR2024	03MAY2024	280	65	1700	11
12	Mark	Germany	10APR2024	06MAY2024	260	60	1550	12

2.DATE FUNCTIONS PRACTICE

2.1 Months Active Using INTCK

data work.player_duration;

    set gaming_players;

    Months_Active = intck('month', Join_Date, Last_Play_Date);

run;

proc print data=work.player_duration;

run;

OUTPUT:

Obs	Player_Name	Country	Join_Date	Last_Play_Date	Hours_Played	Wins	Kills	Rank	Months_Active
1	Alex	USA	01JAN2024	22FEB2024	520	120	3400	1	1
2	Ravi	India	15JAN2024	03MAR2024	480	110	3100	2	2
3	Chen	China	01FEB2024	18MAR2024	460	105	2950	3	1
4	Carlos	Brazil	10FEB2024	24MAR2024	430	98	2700	4	1
5	Ivan	Russia	20FEB2024	01APR2024	410	95	2600	5	2
6	Leo	France	01MAR2024	09APR2024	390	90	2450	6	1
7	Sam	UK	10MAR2024	15APR2024	360	85	2300	7	1
8	Noah	Canada	15MAR2024	18APR2024	340	80	2150	8	1
9	Ali	UAE	20MAR2024	21APR2024	320	75	2000	9	1
10	Tom	Australia	01APR2024	01MAY2024	300	70	1850	10	1
11	Ken	Japan	05APR2024	03MAY2024	280	65	1700	11	1
12	Mark	Germany	10APR2024	06MAY2024	260	60	1550	12	1

2.2 Generating a Fixed Tournament Date Using MDY

data work.tournament;

    set gaming_players;

    Tournament_Date = mdy(6, 15, 2024);

    format Tournament_Date date9.;

run;

proc print data=work.tournament;

run;

OUTPUT:

Obs	Player_Name	Country	Join_Date	Last_Play_Date	Hours_Played	Wins	Kills	Rank	Tournament_Date
1	Alex	USA	01JAN2024	22FEB2024	520	120	3400	1	15JUN2024
2	Ravi	India	15JAN2024	03MAR2024	480	110	3100	2	15JUN2024
3	Chen	China	01FEB2024	18MAR2024	460	105	2950	3	15JUN2024
4	Carlos	Brazil	10FEB2024	24MAR2024	430	98	2700	4	15JUN2024
5	Ivan	Russia	20FEB2024	01APR2024	410	95	2600	5	15JUN2024
6	Leo	France	01MAR2024	09APR2024	390	90	2450	6	15JUN2024
7	Sam	UK	10MAR2024	15APR2024	360	85	2300	7	15JUN2024
8	Noah	Canada	15MAR2024	18APR2024	340	80	2150	8	15JUN2024
9	Ali	UAE	20MAR2024	21APR2024	320	75	2000	9	15JUN2024
10	Tom	Australia	01APR2024	01MAY2024	300	70	1850	10	15JUN2024
11	Ken	Japan	05APR2024	03MAY2024	280	65	1700	11	15JUN2024
12	Mark	Germany	10APR2024	06MAY2024	260	60	1550	12	15JUN2024

3.PROC SQL – DATA QUERY & DERIVED METRICS

3.1 Calculating Kill Efficiency

proc sql;

    create table work.player_efficiency as

    select Player_Name,Country,Hours_Played,Kills,Wins,

           (Kills / Hours_Played) as Kill_Rate format=8.2

    from gaming_players

    order by Kill_Rate desc;

quit;

proc print data=work.player_efficiency;

run;

OUTPUT:

Obs	Player_Name	Country	Hours_Played	Kills	Wins	Kill_Rate
1	Alex	USA	520	3400	120	6.54
2	Ravi	India	480	3100	110	6.46
3	Chen	China	460	2950	105	6.41
4	Sam	UK	360	2300	85	6.39
5	Ivan	Russia	410	2600	95	6.34
6	Noah	Canada	340	2150	80	6.32
7	Leo	France	390	2450	90	6.28
8	Carlos	Brazil	430	2700	98	6.28
9	Ali	UAE	320	2000	75	6.25
10	Tom	Australia	300	1850	70	6.17
11	Ken	Japan	280	1700	65	6.07
12	Mark	Germany	260	1550	60	5.96

4.PROC MEANS – STATISTICAL SUMMARY

proc means data=gaming_players mean min max;

    var Hours_Played Wins Kills Rank;

run;

OUTPUT:

The MEANS Procedure

Variable	Mean	Minimum	Maximum
Hours_Played Wins Kills Rank	379.1666667 87.7500000 2395.83 6.5000000	260.0000000 60.0000000 1550.00 1.0000000	520.0000000 120.0000000 3400.00 12.0000000

5.PROC UNIVARIATE – DISTRIBUTION ANALYSIS

proc univariate data=gaming_players;

    var Kills;

    histogram Kills;

run;

OUTPUT:

The UNIVARIATE Procedure

Variable: Kills

Moments
N	12	Sum Weights	12
Mean	2395.83333	Sum Observations	28750
Std Deviation	577.792953	Variance	333844.697
Skewness	0.2184608	Kurtosis	-0.8796393
Uncorrected SS	72552500	Corrected SS	3672291.67
Coeff Variation	24.1165754	Std Error Mean	166.794459

Basic Statistical Measures
Location		Variability
Mean	2395.833	Std Deviation	577.79295
Median	2375.000	Variance	333845
Mode	.	Range	1850
		Interquartile Range	900.00000

Tests for Location: Mu0=0
Test	Statistic		p Value
Student's t	t	14.36399	Pr > |t|	<.0001
Sign	M	6	Pr >= |M|	0.0005
Signed Rank	S	39	Pr >= |S|	0.0005

Quantiles (Definition 5)
Level	Quantile
100% Max	3400
99%	3400
95%	3400
90%	3100
75% Q3	2825
50% Median	2375
25% Q1	1925
10%	1700
5%	1550
1%	1550
0% Min	1550

Extreme Observations
Lowest		Highest
Value	Obs	Value	Obs
1550	12	2600	5
1700	11	2700	4
1850	10	2950	3
2000	9	3100	2
2150	8	3400	1

The UNIVARIATE Procedure

6.PROC SGPLOT – DATA VISUALIZATION

6.1 Hours Played vs Wins

proc sgplot data=gaming_players;

    scatter x=Hours_Played y=Wins;

    title "Hours Played vs Wins";

run;

OUTPUT:

7.MACRO – AUTOMATED PLAYER RANKING

%macro player_category;

    data work.player_category;

        set gaming_players;

        length Player_Level $15;

        

        if Rank <= 3 then Player_Level = "Elite";

        else if Rank <= 7 then Player_Level = "Pro";

        else Player_Level = "Beginner";

    run;

proc print data=work.player_category;

    run;

%mend;

%player_category;

OUTPUT:

Obs	Player_Name	Country	Join_Date	Last_Play_Date	Hours_Played	Wins	Kills	Rank	Player_Level
1	Alex	USA	01JAN2024	22FEB2024	520	120	3400	1	Elite
2	Ravi	India	15JAN2024	03MAR2024	480	110	3100	2	Elite
3	Chen	China	01FEB2024	18MAR2024	460	105	2950	3	Elite
4	Carlos	Brazil	10FEB2024	24MAR2024	430	98	2700	4	Pro
5	Ivan	Russia	20FEB2024	01APR2024	410	95	2600	5	Pro
6	Leo	France	01MAR2024	09APR2024	390	90	2450	6	Pro
7	Sam	UK	10MAR2024	15APR2024	360	85	2300	7	Pro
8	Noah	Canada	15MAR2024	18APR2024	340	80	2150	8	Beginner
9	Ali	UAE	20MAR2024	21APR2024	320	75	2000	9	Beginner
10	Tom	Australia	01APR2024	01MAY2024	300	70	1850	10	Beginner
11	Ken	Japan	05APR2024	03MAY2024	280	65	1700	11	Beginner
12	Mark	Germany	10APR2024	06MAY2024	260	60	1550	12	Beginner

8.PROC APPEND – ADDITIONAL PLAYERS

data work.new_players;

    length Player_Name $20 Country $15;

    format Join_Date date9.;

    input Player_Name $ Country $ Hours_Played Wins Kills Rank Join_Date :date9.;

    datalines;

Zane USA 200 45 1200 13 15APR2024

;

run;

proc print data=work.new_players;

run;

OUTPUT:

Obs	Player_Name	Country	Join_Date	Hours_Played	Wins	Kills	Rank
1	Zane	USA	15APR2024	200	45	1200	13

proc append base=gaming_players 

            data=new_players force;

run;

proc print data=work.gaming_players;

run;

OUTPUT:

Obs	Player_Name	Country	Join_Date	Last_Play_Date	Hours_Played	Wins	Kills	Rank
1	Alex	USA	01JAN2024	22FEB2024	520	120	3400	1
2	Ravi	India	15JAN2024	03MAR2024	480	110	3100	2
3	Chen	China	01FEB2024	18MAR2024	460	105	2950	3
4	Carlos	Brazil	10FEB2024	24MAR2024	430	98	2700	4
5	Ivan	Russia	20FEB2024	01APR2024	410	95	2600	5
6	Leo	France	01MAR2024	09APR2024	390	90	2450	6
7	Sam	UK	10MAR2024	15APR2024	360	85	2300	7
8	Noah	Canada	15MAR2024	18APR2024	340	80	2150	8
9	Ali	UAE	20MAR2024	21APR2024	320	75	2000	9
10	Tom	Australia	01APR2024	01MAY2024	300	70	1850	10
11	Ken	Japan	05APR2024	03MAY2024	280	65	1700	11
12	Mark	Germany	10APR2024	06MAY2024	260	60	1550	12
13	Zane	USA	15APR2024	.	200	45	1200	13

9.PROC MERGE – COMBINING DATASETS

proc sort data=gaming_players; by Player_Name; run;

proc print data=work.gaming_players;

run;

OUTPUT:

Obs	Player_Name	Country	Join_Date	Last_Play_Date	Hours_Played	Wins	Kills	Rank
1	Alex	USA	01JAN2024	22FEB2024	520	120	3400	1
2	Ali	UAE	20MAR2024	21APR2024	320	75	2000	9
3	Carlos	Brazil	10FEB2024	24MAR2024	430	98	2700	4
4	Chen	China	01FEB2024	18MAR2024	460	105	2950	3
5	Ivan	Russia	20FEB2024	01APR2024	410	95	2600	5
6	Ken	Japan	05APR2024	03MAY2024	280	65	1700	11
7	Leo	France	01MAR2024	09APR2024	390	90	2450	6
8	Mark	Germany	10APR2024	06MAY2024	260	60	1550	12
9	Noah	Canada	15MAR2024	18APR2024	340	80	2150	8
10	Ravi	India	15JAN2024	03MAR2024	480	110	3100	2
11	Sam	UK	10MAR2024	15APR2024	360	85	2300	7
12	Tom	Australia	01APR2024	01MAY2024	300	70	1850	10
13	Zane	USA	15APR2024	.	200	45	1200	13

proc sort data=player_category; by Player_Name; run;

proc print data=work.player_category;

run;

OUTPUT:

Obs	Player_Name	Country	Join_Date	Last_Play_Date	Hours_Played	Wins	Kills	Rank	Player_Level
1	Alex	USA	01JAN2024	22FEB2024	520	120	3400	1	Elite
2	Ali	UAE	20MAR2024	21APR2024	320	75	2000	9	Beginner
3	Carlos	Brazil	10FEB2024	24MAR2024	430	98	2700	4	Pro
4	Chen	China	01FEB2024	18MAR2024	460	105	2950	3	Elite
5	Ivan	Russia	20FEB2024	01APR2024	410	95	2600	5	Pro
6	Ken	Japan	05APR2024	03MAY2024	280	65	1700	11	Beginner
7	Leo	France	01MAR2024	09APR2024	390	90	2450	6	Pro
8	Mark	Germany	10APR2024	06MAY2024	260	60	1550	12	Beginner
9	Noah	Canada	15MAR2024	18APR2024	340	80	2150	8	Beginner
10	Ravi	India	15JAN2024	03MAR2024	480	110	3100	2	Elite
11	Sam	UK	10MAR2024	15APR2024	360	85	2300	7	Pro
12	Tom	Australia	01APR2024	01MAY2024	300	70	1850	10	Beginner

data work.player_full;

    merge gaming_players player_category;

    by Player_Name;

run;

proc print data=work.player_full;

run;

OUTPUT:

Obs	Player_Name	Country	Join_Date	Last_Play_Date	Hours_Played	Wins	Kills	Rank	Player_Level
1	Alex	USA	01JAN2024	22FEB2024	520	120	3400	1	Elite
2	Ali	UAE	20MAR2024	21APR2024	320	75	2000	9	Beginner
3	Carlos	Brazil	10FEB2024	24MAR2024	430	98	2700	4	Pro
4	Chen	China	01FEB2024	18MAR2024	460	105	2950	3	Elite
5	Ivan	Russia	20FEB2024	01APR2024	410	95	2600	5	Pro
6	Ken	Japan	05APR2024	03MAY2024	280	65	1700	11	Beginner
7	Leo	France	01MAR2024	09APR2024	390	90	2450	6	Pro
8	Mark	Germany	10APR2024	06MAY2024	260	60	1550	12	Beginner
9	Noah	Canada	15MAR2024	18APR2024	340	80	2150	8	Beginner
10	Ravi	India	15JAN2024	03MAR2024	480	110	3100	2	Elite
11	Sam	UK	10MAR2024	15APR2024	360	85	2300	7	Pro
12	Tom	Australia	01APR2024	01MAY2024	300	70	1850	10	Beginner
13	Zane	USA	15APR2024	.	200	45	1200	13

10.PROC TRANSPOSE – STRUCTURAL TRANSFORMATION

proc transpose data=gaming_players out=work.transposed_kills;

    by Country NotSorted;

    var Kills;

run;

proc print data=work.transposed_kills;

run;

OUTPUT:

Obs	Country	_NAME_	COL1
1	USA	Kills	3400
2	UAE	Kills	2000
3	Brazil	Kills	2700
4	China	Kills	2950
5	Russia	Kills	2600
6	Japan	Kills	1700
7	France	Kills	2450
8	Germany	Kills	1550
9	Canada	Kills	2150
10	India	Kills	3100
11	UK	Kills	2300
12	Australia	Kills	1850
13	USA	Kills	1200

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