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

on
0

200.SAS ELECTRONICS DATA ANALYSIS USING PROC PRINT | PROC MEANS | PROC FREQ | PROC SQL | PROC REPORT | PROC FORMAT | PROC SGPLOT | PROC RANK | PROC EXPORT | PROC TRANSPOSE | PROC UNIVARIATE | PROC TABULATE

on

SAS ELECTRONICS DATA ANALYSIS USING PROC PRINT | PROC MEANS | PROC FREQ | PROC SQL | PROC REPORT | PROC FORMAT | PROC SGPLOT | PROC RANK | PROC EXPORT | PROC TRANSPOSE | PROC UNIVARIATE | PROC TABULATE

/*A unique and creative SAS project involving different types of electronics*/

Step 1: Create Electronics Dataset

data Electronics_Data;

    length Product_ID $5 Product_Name $20 Category $15 Brand $15 Availability $10;

    input Product_ID $ Product_Name $ Category $ Brand $ Price Warranty_Years 

          Power_Consumption Weight Ratings Availability $ Launch_Year;

    datalines;

E001 Galaxy_S21 Mobile Samsung 69999 2 15 0.169 4.5 InStock 2021

E002 MacBook_Pro Laptop Apple 129999 3 65 1.4 4.8 InStock 2022

E003 Bravia_4K TV Sony 84999 2 110 8.0 4.4 OutOfStock 2020

E004 Mi_Band_6 Watch Xiaomi 3499 1 5 0.035 4.2 InStock 2021

E005 Surface_Pro Tablet Microsoft 99999 2 30 0.8 4.6 InStock 2023

E006 JBL_Flip5 Speaker JBL 6999 1 10 0.5 4.3 InStock 2020

E007 OnePlus_9 Mobile OnePlus 49999 2 18 0.197 4.4 InStock 2021

E008 ThinkPad_X1 Laptop Lenovo 114999 3 60 1.2 4.7 OutOfStock 2022

E009 OLED_TV TV LG 134999 2 120 9.5 4.6 InStock 2021

E010 Galaxy_Tab Tablet Samsung 54999 2 20 0.6 4.1 InStock 2022

E011 iPhone_13 Mobile Apple 79999 2 17 0.174 4.9 InStock 2022

E012 Pixel_6 Mobile Google 59999 2 16 0.178 4.5 OutOfStock 2021

E013 Echo_Dot Speaker Amazon 3499 1 6 0.3 4.2 InStock 2020

E014 Realme_Book Laptop Realme 49999 2 55 1.3 4.0 InStock 2023

E015 QLED_TV TV TCL 74999 2 100 7.5 4.3 InStock 2022

E016 iPad_Pro Tablet Apple 109999 2 25 0.7 4.8 OutOfStock 2023

E017 Watch_Series_7 Watch Apple 41999 2 6 0.042 4.6 InStock 2022

;

run;

proc print;run;

Output:

Obs Product_ID Product_Name Category Brand Availability Price Warranty_Years Power_Consumption Weight Ratings Launch_Year
1 E001 Galaxy_S21 Mobile Samsung InStock 69999 2 15 0.169 4.5 2021
2 E002 MacBook_Pro Laptop Apple InStock 129999 3 65 1.400 4.8 2022
3 E003 Bravia_4K TV Sony OutOfStock 84999 2 110 8.000 4.4 2020
4 E004 Mi_Band_6 Watch Xiaomi InStock 3499 1 5 0.035 4.2 2021
5 E005 Surface_Pro Tablet Microsoft InStock 99999 2 30 0.800 4.6 2023
6 E006 JBL_Flip5 Speaker JBL InStock 6999 1 10 0.500 4.3 2020
7 E007 OnePlus_9 Mobile OnePlus InStock 49999 2 18 0.197 4.4 2021
8 E008 ThinkPad_X1 Laptop Lenovo OutOfStock 114999 3 60 1.200 4.7 2022
9 E009 OLED_TV TV LG InStock 134999 2 120 9.500 4.6 2021
10 E010 Galaxy_Tab Tablet Samsung InStock 54999 2 20 0.600 4.1 2022
11 E011 iPhone_13 Mobile Apple InStock 79999 2 17 0.174 4.9 2022
12 E012 Pixel_6 Mobile Google OutOfStock 59999 2 16 0.178 4.5 2021
13 E013 Echo_Dot Speaker Amazon InStock 3499 1 6 0.300 4.2 2020
14 E014 Realme_Book Laptop Realme InStock 49999 2 55 1.300 4.0 2023
15 E015 QLED_TV TV TCL InStock 74999 2 100 7.500 4.3 2022
16 E016 iPad_Pro Tablet Apple OutOfStock 109999 2 25 0.700 4.8 2023
17 E017 Watch_Series_7 Watch Apple InStock 41999 2 6 0.042 4.6 2022


Step 2: PROC CONTENTS and PROC PRINT

proc contents data=Electronics_Data;

    title "Structure of Electronics Dataset";

run;

Output:

Structure of Electronics Dataset

The CONTENTS Procedure

Data Set Name WORK.ELECTRONICS_DATA Observations 17
Member Type DATA Variables 11
Engine V9 Indexes 0
Created 14/09/2015 00:03:19 Observation Length 120
Last Modified 14/09/2015 00:03:19 Deleted Observations 0
Protection   Compressed NO
Data Set Type   Sorted NO
Label      
Data Representation WINDOWS_64    
Encoding wlatin1 Western (Windows)    


Engine/Host Dependent Information
Data Set Page Size 65536
Number of Data Set Pages 1
First Data Page 1
Max Obs per Page 545
Obs in First Data Page 17
Number of Data Set Repairs 0
ExtendObsCounter YES
Filename C:\Users\Lenovo\AppData\Local\Temp\SAS Temporary Files\_TD2096_DESKTOP-QFAA4KV_\electronics_data.sas7bdat
Release Created 9.0401M2
Host Created X64_8HOME


Alphabetic List of Variables and Attributes
# Variable Type Len
5 Availability Char 10
4 Brand Char 15
3 Category Char 15
11 Launch_Year Num 8
8 Power_Consumption Num 8
6 Price Num 8
1 Product_ID Char 5
2 Product_Name Char 20
10 Ratings Num 8
7 Warranty_Years Num 8
9 Weight Num 8


proc print data=Electronics_Data;

    title "Complete Electronics Dataset";

run;

Output:

Complete Electronics Dataset

Obs Product_ID Product_Name Category Brand Availability Price Warranty_Years Power_Consumption Weight Ratings Launch_Year
1 E001 Galaxy_S21 Mobile Samsung InStock 69999 2 15 0.169 4.5 2021
2 E002 MacBook_Pro Laptop Apple InStock 129999 3 65 1.400 4.8 2022
3 E003 Bravia_4K TV Sony OutOfStock 84999 2 110 8.000 4.4 2020
4 E004 Mi_Band_6 Watch Xiaomi InStock 3499 1 5 0.035 4.2 2021
5 E005 Surface_Pro Tablet Microsoft InStock 99999 2 30 0.800 4.6 2023
6 E006 JBL_Flip5 Speaker JBL InStock 6999 1 10 0.500 4.3 2020
7 E007 OnePlus_9 Mobile OnePlus InStock 49999 2 18 0.197 4.4 2021
8 E008 ThinkPad_X1 Laptop Lenovo OutOfStock 114999 3 60 1.200 4.7 2022
9 E009 OLED_TV TV LG InStock 134999 2 120 9.500 4.6 2021
10 E010 Galaxy_Tab Tablet Samsung InStock 54999 2 20 0.600 4.1 2022
11 E011 iPhone_13 Mobile Apple InStock 79999 2 17 0.174 4.9 2022
12 E012 Pixel_6 Mobile Google OutOfStock 59999 2 16 0.178 4.5 2021
13 E013 Echo_Dot Speaker Amazon InStock 3499 1 6 0.300 4.2 2020
14 E014 Realme_Book Laptop Realme InStock 49999 2 55 1.300 4.0 2023
15 E015 QLED_TV TV TCL InStock 74999 2 100 7.500 4.3 2022
16 E016 iPad_Pro Tablet Apple OutOfStock 109999 2 25 0.700 4.8 2023
17 E017 Watch_Series_7 Watch Apple InStock 41999 2 6 0.042 4.6 2022


Step 3: PROC MEANS and PROC FREQ

proc means data=Electronics_Data mean std min max;

    var Price Warranty_Years Power_Consumption Weight Ratings;

    title "Descriptive Statistics of Electronics Variables";

run;

Output:

Descriptive Statistics of Electronics Variables

The MEANS Procedure

Variable Mean Std Dev Minimum Maximum
Price
Warranty_Years
Power_Consumption
Weight
Ratings
68881.35
1.9411765
39.8823529
1.9173529
4.4647059
41383.32
0.5557189
38.3452773
3.1130391
0.2596661
3499.00
1.0000000
5.0000000
0.0350000
4.0000000
134999.00
3.0000000
120.0000000
9.5000000
4.9000000

proc freq data=Electronics_Data;

    tables Category Brand Availability / nocum nopercent;

    title "Frequency of Electronics by Category, Brand, and Availability";

run;

Output:

Frequency of Electronics by Category, Brand, and Availability

The FREQ Procedure

Category Frequency
Laptop 3
Mobile 4
Speaker 2
TV 3
Tablet 3
Watch 2


Brand Frequency
Amazon 1
Apple 4
Google 1
JBL 1
LG 1
Lenovo 1
Microsoft 1
OnePlus 1
Realme 1
Samsung 2
Sony 1
TCL 1
Xiaomi 1


Availability Frequency
InStock 13
OutOfStock 4


Step 4: PROC SORT and PROC UNIVARIATE

proc sort data=Electronics_Data out=Sorted_Electronics;

    by descending Price;

run;

proc print;run;

Output:

Obs Product_ID Product_Name Category Brand Availability Price Warranty_Years Power_Consumption Weight Ratings Launch_Year
1 E009 OLED_TV TV LG InStock 134999 2 120 9.500 4.6 2021
2 E002 MacBook_Pro Laptop Apple InStock 129999 3 65 1.400 4.8 2022
3 E008 ThinkPad_X1 Laptop Lenovo OutOfStock 114999 3 60 1.200 4.7 2022
4 E016 iPad_Pro Tablet Apple OutOfStock 109999 2 25 0.700 4.8 2023
5 E005 Surface_Pro Tablet Microsoft InStock 99999 2 30 0.800 4.6 2023
6 E003 Bravia_4K TV Sony OutOfStock 84999 2 110 8.000 4.4 2020
7 E011 iPhone_13 Mobile Apple InStock 79999 2 17 0.174 4.9 2022
8 E015 QLED_TV TV TCL InStock 74999 2 100 7.500 4.3 2022
9 E001 Galaxy_S21 Mobile Samsung InStock 69999 2 15 0.169 4.5 2021
10 E012 Pixel_6 Mobile Google OutOfStock 59999 2 16 0.178 4.5 2021
11 E010 Galaxy_Tab Tablet Samsung InStock 54999 2 20 0.600 4.1 2022
12 E007 OnePlus_9 Mobile OnePlus InStock 49999 2 18 0.197 4.4 2021
13 E014 Realme_Book Laptop Realme InStock 49999 2 55 1.300 4.0 2023
14 E017 Watch_Series_7 Watch Apple InStock 41999 2 6 0.042 4.6 2022
15 E006 JBL_Flip5 Speaker JBL InStock 6999 1 10 0.500 4.3 2020
16 E004 Mi_Band_6 Watch Xiaomi InStock 3499 1 5 0.035 4.2 2021
17 E013 Echo_Dot Speaker Amazon InStock 3499 1 6 0.300 4.2 2020


proc univariate data=Electronics_Data;

    var Ratings;

    histogram Ratings / normal;

    title "Distribution of Product Ratings";

run;

Output:

Distribution of Product Ratings

The UNIVARIATE Procedure
Fitted Normal Distribution for Ratings

Parameters for Normal Distribution
Parameter Symbol Estimate
Mean Mu 4.464706
Std Dev Sigma 0.259666


Goodness-of-Fit Tests for Normal Distribution
Test Statistic p Value
Kolmogorov-Smirnov D 0.11059218 Pr > D >0.150
Cramer-von Mises W-Sq 0.02806871 Pr > W-Sq >0.250
Anderson-Darling A-Sq 0.18511997 Pr > A-Sq >0.250


Quantiles for Normal Distribution
Percent Quantile
Observed Estimated
1.0 4.00000 3.86063
5.0 4.00000 4.03759
10.0 4.10000 4.13193
25.0 4.30000 4.28956
50.0 4.50000 4.46471
75.0 4.60000 4.63985
90.0 4.80000 4.79748
95.0 4.90000 4.89182
99.0 4.90000 5.06878


Step 5: PROC SQL - Advanced Queries

proc sql;

    create table AvgPrice_Category as

    select Category, mean(Price) as Avg_Price

    from Electronics_Data

    group by Category;


    create table Top_Rated as

    select Product_Name, Category, Ratings

    from Electronics_Data

    where Ratings > 4.6;


    create table High_Consumption as

    select * from Electronics_Data

    where Power_Consumption > 50;


    create table No_Of_Brands  as

    select Brand, count(*) as Product_Count

    from Electronics_Data

    group by Brand;

quit;

proc print data=AvgPrice_Category;

run;

Output:

Obs Category Avg_Price
1 Laptop 98332.33
2 Mobile 64999.00
3 Speaker 5249.00
4 TV 98332.33
5 Tablet 88332.33
6 Watch 22749.00


proc print data=Top_Rated;

run;

Output:

Obs Product_Name Category Ratings
1 MacBook_Pro Laptop 4.8
2 ThinkPad_X1 Laptop 4.7
3 iPhone_13 Mobile 4.9
4 iPad_Pro Tablet 4.8


proc print data=High_Consumption;

run;

Output:

Obs Product_ID Product_Name Category Brand Availability Price Warranty_Years Power_Consumption Weight Ratings Launch_Year
1 E002 MacBook_Pro Laptop Apple InStock 129999 3 65 1.4 4.8 2022
2 E003 Bravia_4K TV Sony OutOfStock 84999 2 110 8.0 4.4 2020
3 E008 ThinkPad_X1 Laptop Lenovo OutOfStock 114999 3 60 1.2 4.7 2022
4 E009 OLED_TV TV LG InStock 134999 2 120 9.5 4.6 2021
5 E014 Realme_Book Laptop Realme InStock 49999 2 55 1.3 4.0 2023
6 E015 QLED_TV TV TCL InStock 74999 2 100 7.5 4.3 2022


proc print data=No_Of_Brands;

run;

Output:

Obs Brand Product_Count
1 Amazon 1
2 Apple 4
3 Google 1
4 JBL 1
5 LG 1
6 Lenovo 1
7 Microsoft 1
8 OnePlus 1
9 Realme 1
10 Samsung 2
11 Sony 1
12 TCL 1
13 Xiaomi 1

Step 6: SAS MACRO for Reusability

%macro TopDevices(cat=, n=5);

    proc sql outobs=&n;

        title "Top &n Expensive Devices in &cat Category";

        select Product_Name, Price

        from Electronics_Data

        where Category = "&cat"

        order by Price desc;

    quit;

%mend;


%TopDevices(cat=Mobile, n=3);

Output:

Top 3 Expensive Devices in Mobile Category

Product_Name Price
iPhone_13 79999
Galaxy_S21 69999
Pixel_6 59999


%TopDevices(cat=TV, n=2);

Output:

Top 2 Expensive Devices in TV Category

Product_Name Price
OLED_TV 134999
Bravia_4K 84999


Step 7: PROC REPORT and PROC TABULATE

proc report data=Electronics_Data nowd;

    column Category Brand Price Ratings;

    define Category / group;

    define Brand / group;

    define Price / analysis mean;

    define Ratings / analysis mean;

    title "Average Price and Ratings by Brand and Category";

run;

Output:

Average Price and Ratings by Brand and Category

Category Brand Price Ratings
Laptop Apple 129999 4.8
  Lenovo 114999 4.7
  Realme 49999 4
Mobile Apple 79999 4.9
  Google 59999 4.5
  OnePlus 49999 4.4
  Samsung 69999 4.5
Speaker Amazon 3499 4.2
  JBL 6999 4.3
TV LG 134999 4.6
  Sony 84999 4.4
  TCL 74999 4.3
Tablet Apple 109999 4.8
  Microsoft 99999 4.6
  Samsung 54999 4.1
Watch Apple 41999 4.6
  Xiaomi 3499 4.2


proc tabulate data=Electronics_Data;

    class Category Brand;

    var Price Ratings;

    table Category, Brand*(Price Ratings)*mean;

    title "Tabular View of Mean Price and Ratings";

run;

Output:

Tabular View of Mean Price and Ratings

  Brand
Amazon Apple Google JBL LG Lenovo Microsoft OnePlus Realme Samsung Sony TCL Xiaomi
Price Ratings Price Ratings Price Ratings Price Ratings Price Ratings Price Ratings Price Ratings Price Ratings Price Ratings Price Ratings Price Ratings Price Ratings Price Ratings
Mean Mean Mean Mean Mean Mean Mean Mean Mean Mean Mean Mean Mean Mean Mean Mean Mean Mean Mean Mean Mean Mean Mean Mean Mean Mean
Category . . 129999.00 4.80 . . . . . . 114999.00 4.70 . . . . 49999.00 4.00 . . . . . . . .
Laptop
Mobile . . 79999.00 4.90 59999.00 4.50 . . . . . . . . 49999.00 4.40 . . 69999.00 4.50 . . . . . .
Speaker 3499.00 4.20 . . . . 6999.00 4.30 . . . . . . . . . . . . . . . . . .
TV . . . . . . . . 134999.00 4.60 . . . . . . . . . . 84999.00 4.40 74999.00 4.30 . .
Tablet . . 109999.00 4.80 . . . . . . . . 99999.00 4.60 . . . . 54999.00 4.10 . . . . . .
Watch . . 41999.00 4.60 . . . . . . . . . . . . . . . . . . . . 3499.00 4.20


Step 8: PROC FORMAT and DATA Manipulation

proc format;

    value $stockfmt

        'InStock' = 'Available'

        'OutOfStock' = 'Not Available';

    value ratingfmt

        low-4 = 'Low'

        4<-4.5 = 'Medium'

        4.5<-5 = 'High';

run;


data Electronics_Formatted;

    set Electronics_Data;

    format Availability $stockfmt. Ratings ratingfmt.;

run;

proc print data=Electronics_Formatted;

    title "Electronics Dataset with Custom Formats";

run;

Output:

Electronics Dataset with Custom Formats

Obs Product_ID Product_Name Category Brand Availability Price Warranty_Years Power_Consumption Weight Ratings Launch_Year
1 E001 Galaxy_S21 Mobile Samsung Available 69999 2 15 0.169 Medium 2021
2 E002 MacBook_Pro Laptop Apple Available 129999 3 65 1.400 High 2022
3 E003 Bravia_4K TV Sony Not Available 84999 2 110 8.000 Medium 2020
4 E004 Mi_Band_6 Watch Xiaomi Available 3499 1 5 0.035 Medium 2021
5 E005 Surface_Pro Tablet Microsoft Available 99999 2 30 0.800 High 2023
6 E006 JBL_Flip5 Speaker JBL Available 6999 1 10 0.500 Medium 2020
7 E007 OnePlus_9 Mobile OnePlus Available 49999 2 18 0.197 Medium 2021
8 E008 ThinkPad_X1 Laptop Lenovo Not Available 114999 3 60 1.200 High 2022
9 E009 OLED_TV TV LG Available 134999 2 120 9.500 High 2021
10 E010 Galaxy_Tab Tablet Samsung Available 54999 2 20 0.600 Medium 2022
11 E011 iPhone_13 Mobile Apple Available 79999 2 17 0.174 High 2022
12 E012 Pixel_6 Mobile Google Not Available 59999 2 16 0.178 Medium 2021
13 E013 Echo_Dot Speaker Amazon Available 3499 1 6 0.300 Medium 2020
14 E014 Realme_Book Laptop Realme Available 49999 2 55 1.300 Low 2023
15 E015 QLED_TV TV TCL Available 74999 2 100 7.500 Medium 2022
16 E016 iPad_Pro Tablet Apple Not Available 109999 2 25 0.700 High 2023
17 E017 Watch_Series_7 Watch Apple Available 41999 2 6 0.042 High 2022


Step 9: PROC SGPLOT - Visualization

proc sgplot data=Electronics_Data;

    vbar Category / response=Price stat=mean;

    title "Average Price by Electronics Category";

run;

Log:

NOTE: PROCEDURE SGPLOT used (Total process time):

      real time           0.71 seconds

      cpu time            0.10 seconds


NOTE: Listing image output written to SGPlot1.png.

NOTE: There were 17 observations read from the data set WORK.ELECTRONICS_DATA.


proc sgplot data=Electronics_Data;

    scatter x=Power_Consumption y=Ratings / group=Category;

    title "Power vs Ratings by Category";

run;

Output:

NOTE: PROCEDURE SGPLOT used (Total process time):

      real time           0.48 seconds

      cpu time            0.13 seconds


NOTE: Listing image output written to SGPlot3.png.

NOTE: There were 17 observations read from the data set WORK.ELECTRONICS_DATA.


Step 10: PROC TRANSPOSE and PROC RANK

proc sort data=Electronics_Data out=Sorted_Electronics;

    by Product_ID;

run;


proc transpose data=Sorted_Electronics out=Transposed prefix=Device_;

    by Product_ID;

    id Category;

    var Price;

run;

proc print;run;

Output:

Obs Product_ID _NAME_ Device_Mobile Device_Laptop Device_TV Device_Watch Device_Tablet Device_Speaker
1 E001 Price 69999 . . . . .
2 E002 Price . 129999 . . . .
3 E003 Price . . 84999 . . .
4 E004 Price . . . 3499 . .
5 E005 Price . . . . 99999 .
6 E006 Price . . . . . 6999
7 E007 Price 49999 . . . . .
8 E008 Price . 114999 . . . .
9 E009 Price . . 134999 . . .
10 E010 Price . . . . 54999 .
11 E011 Price 79999 . . . . .
12 E012 Price 59999 . . . . .
13 E013 Price . . . . . 3499
14 E014 Price . 49999 . . . .
15 E015 Price . . 74999 . . .
16 E016 Price . . . . 109999 .
17 E017 Price . . . 41999 . .


proc rank data=Electronics_Data out=Ranked descending ties=low;

    var Ratings;

    ranks Rating_Rank;

run;

proc print data=Ranked;

    title "Products Ranked by Ratings";

run;

Output:

Products Ranked by Ratings

Obs Product_ID Product_Name Category Brand Availability Price Warranty_Years Power_Consumption Weight Ratings Launch_Year Rating_Rank
1 E001 Galaxy_S21 Mobile Samsung InStock 69999 2 15 0.169 4.5 2021 8
2 E002 MacBook_Pro Laptop Apple InStock 129999 3 65 1.400 4.8 2022 2
3 E003 Bravia_4K TV Sony OutOfStock 84999 2 110 8.000 4.4 2020 10
4 E004 Mi_Band_6 Watch Xiaomi InStock 3499 1 5 0.035 4.2 2021 14
5 E005 Surface_Pro Tablet Microsoft InStock 99999 2 30 0.800 4.6 2023 5
6 E006 JBL_Flip5 Speaker JBL InStock 6999 1 10 0.500 4.3 2020 12
7 E007 OnePlus_9 Mobile OnePlus InStock 49999 2 18 0.197 4.4 2021 10
8 E008 ThinkPad_X1 Laptop Lenovo OutOfStock 114999 3 60 1.200 4.7 2022 4
9 E009 OLED_TV TV LG InStock 134999 2 120 9.500 4.6 2021 5
10 E010 Galaxy_Tab Tablet Samsung InStock 54999 2 20 0.600 4.1 2022 16
11 E011 iPhone_13 Mobile Apple InStock 79999 2 17 0.174 4.9 2022 1
12 E012 Pixel_6 Mobile Google OutOfStock 59999 2 16 0.178 4.5 2021 8
13 E013 Echo_Dot Speaker Amazon InStock 3499 1 6 0.300 4.2 2020 14
14 E014 Realme_Book Laptop Realme InStock 49999 2 55 1.300 4.0 2023 17
15 E015 QLED_TV TV TCL InStock 74999 2 100 7.500 4.3 2022 12
16 E016 iPad_Pro Tablet Apple OutOfStock 109999 2 25 0.700 4.8 2023 2
17 E017 Watch_Series_7 Watch Apple InStock 41999 2 6 0.042 4.6 2022 5


Step 11: PROC EXPORT - Export to Excel

proc export data=Electronics_Data

    outfile="Electronics_Report.xlsx"

    dbms=xlsx

    replace;

    sheet="Electronics";

run;

Log:
NOTE: The export data set has 17 observations and 11 variables.
NOTE: "C:\sas folder\SASFoundation\9.4\Electronics_Report.xlsx" file was successfully created.
NOTE: PROCEDURE EXPORT used (Total process time):
      real time           0.61 seconds
      cpu time            0.06 seconds





To Visit My Previous Book Store Dataset:Click Here
To Visit My Previous Festival Dataset:Click Here
To Visit My Previous SQL Joins:Click Here
To Visit My Previous Sas Interview Questions-1:Click Here




PRACTICE AND COMMENT YOUR OUTPUT: 

--->PLEASE FOLLOW OUR BLOG FOR MORE UPDATES.

PLEASE FOLLOW OUR TELEGRAM CHANNEL CLICK HERE

PLEASE FOLLOW OUR FACEBOOK PAGE  CLICK HERE

PLEASE FOLLOW OUR INSTAGRAM PAGE CLICK HERE


Comments

Post a Comment