291.Can Data Predict Election Outcomes? – A Complete SAS Voting Analytics Project

Can Data Predict Election Outcomes? – A Complete SAS Voting Analytics Project

 */Creating A Dataset Of VOTE PROGRAM /*

Step 1: Create a dataset for a vote program 

options nocenter;

data vote_program;

    length VoterID $5 Gender $1 State $15 Party $10 VoteStatus $3;

    input VoterID $ Age Gender $ State $ Party $ VoteStatus $;

    datalines;

V001 25 M Telangana BJP Yes

V002 42 F Andhra Congress No

V003 34 M Telangana Congress Yes

V004 29 F Karnataka BJP Yes

V005 51 M Telangana BJP No

V006 38 F Andhra BJP Yes

V007 46 M Karnataka Congress No

V008 33 F Telangana Congress Yes

V009 27 M Andhra BJP Yes

;

run;

proc print;run;

Output:

Obs	VoterID	Gender	State	Party	VoteStatus	Age
1	V001	M	Telangana	BJP	Yes	25
2	V002	F	Andhra	Congress	No	42
3	V003	M	Telangana	Congress	Yes	34
4	V004	F	Karnataka	BJP	Yes	29
5	V005	M	Telangana	BJP	No	51
6	V006	F	Andhra	BJP	Yes	38
7	V007	M	Karnataka	Congress	No	46
8	V008	F	Telangana	Congress	Yes	33
9	V009	M	Andhra	BJP	Yes	27

Step 2: View the dataset

proc print data=vote_program(obs=7);

    title "Vote Program Dataset";

run;

Output:

Vote Program Dataset

Obs	VoterID	Gender	State	Party	VoteStatus	Age
1	V001	M	Telangana	BJP	Yes	25
2	V002	F	Andhra	Congress	No	42
3	V003	M	Telangana	Congress	Yes	34
4	V004	F	Karnataka	BJP	Yes	29
5	V005	M	Telangana	BJP	No	51
6	V006	F	Andhra	BJP	Yes	38
7	V007	M	Karnataka	Congress	No	46

Step 3: Summary statistics for Age 

proc means data=vote_program mean median min max;

    var Age;

    title "Age Summary Statistics";

run;

Output:

Age Summary Statistics

The MEANS Procedure

Analysis Variable : Age
Mean	Median	Minimum	Maximum
36.1111111	34.0000000	25.0000000	51.0000000

Step 4: Frequency counts for categorical variables 

proc freq data=vote_program;

    tables Gender State Party VoteStatus / nocum;

    title "Frequency Distribution of Categorical Variables";

run;

Output:

Frequency Distribution of Categorical Variables

The FREQ Procedure

Gender	Frequency	Percent
F	4	44.44
M	5	55.56

State	Frequency	Percent
Andhra	3	33.33
Karnataka	2	22.22
Telangana	4	44.44

Party	Frequency	Percent
BJP	5	55.56
Congress	4	44.44

VoteStatus	Frequency	Percent
No	3	33.33
Yes	6	66.67

Step 5: Macro to filter voters by Party and State 

%macro filter_voters(party=, state=);

    proc print data=vote_program;

        where Party="&party" and State="&state";

        title "Voters from &state belonging to &party";

    run;

%mend filter_voters;

Step 6: Use the macro 

%filter_voters(party=BJP, state=Telangana);

Output:

Voters from Telangana belonging to BJP

Obs	VoterID	Gender	State	Party	VoteStatus	Age
1	V001	M	Telangana	BJP	Yes	25
5	V005	M	Telangana	BJP	No	51

%filter_voters(party=Congress, state=Andhra);

Output:

Voters from Andhra belonging to Congress

Obs	VoterID	Gender	State	Party	VoteStatus	Age
2	V002	F	Andhra	Congress	No	42

Step 7: Sort dataset by State and Age 

proc sort data=vote_program out=vote_sorted;

    by State Age;

run;

proc print data=vote_sorted;

    title "Vote Program Dataset Sorted by State and Age";

run;

Output:

Vote Program Dataset Sorted by State and Age

Obs	VoterID	Gender	State	Party	VoteStatus	Age
1	V009	M	Andhra	BJP	Yes	27
2	V006	F	Andhra	BJP	Yes	38
3	V002	F	Andhra	Congress	No	42
4	V004	F	Karnataka	BJP	Yes	29
5	V007	M	Karnataka	Congress	No	46
6	V001	M	Telangana	BJP	Yes	25
7	V008	F	Telangana	Congress	Yes	33
8	V003	M	Telangana	Congress	Yes	34
9	V005	M	Telangana	BJP	No	51

Step 8: Macro to calculate vote percentage by Party 

%macro vote_percentage(party=);

    proc sql;

        select 

            sum(case when VoteStatus='Yes' then 1 else 0 end) as YesVotes,

            count(*) as TotalVotes,

            calculated YesVotes / calculated TotalVotes * 100 as VotePercent format=6.2

        from vote_program

        where Party="&party";

    quit;

%mend vote_percentage;

%vote_percentage(party=BJP);

Output:

YesVotes	TotalVotes	VotePercent
4	5	80.00

%vote_percentage(party=Congress);

Output:

YesVotes	TotalVotes	VotePercent
2	4	50.00

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