Critical Thinking Assignment Data Manipulation of Clothing Store Data In this assignment, you will import the Portfolio_Clothing_store.csv into SAS. (You can find this information by clicking "Next" a

List of variables for Portfolio_Clothing_Store.csv data set

1. Customer id: a unique customer identification number

2. ZIP_CODE: Customer’s zip code

3. FRE: Total number of purchase visits

4. MON: Total net sales

5. CC_CARD: 0 indicates does not use a credit card, 1 indicates the customer uses a credit card

6. AVRG: Average amount spent per visit

7. The following variables contain the percent of total sales spent by the customer on the respective product category:

   1. PSWEATERS: Sweaters

   2. PKNIT_TOPS: Knit tops

   3. PKNIT_DRES: Knit dresses

   4. PBLOUSES: Blouses

   5. PJACKETS: Jackets

   6. PCAR_PNTS: Career pants

   7. PCAS_PNTS: Casual pants

   8. PSHIRTS: Shirts

   9. PDRESSES: Dresses

   10. PSUITS: Suits

   11. POUTERWEAR: Outerwear

   12. PJEWELRY: Jewelry

   13. PFASHION: Fashionable wear

   14. PLEGWEAR: Leg wear

   15. PCOLLSPEND: Collectibles

8. GMP: Gross margin percentage

9. PROMOS: Number of marketing promotions on file

10. DAYS: Number of days the customer has been on file

11. MARKDOWN: Markdown percentage on customer purchases

12. CLUSTYPE: MICROVISION LIFESTYLE CLUSTER TYPE

13. PERCRET: Percent of Returns

14. In days between purchase: Number of days between purchases

15. In lifetime average time between visits in days: Lifetime average time between visits in days.

Six most common lifestyle cluster types in the dataset:

1. Cluster 10 Home Sweet Home: families, medium-high income and education, manager/professionals, technical/sales

2. Cluster 1 Upper Crust: metropolitan families, very high income and education, homeowners, managers/professionals

3. Cluster 4 Mid-life Success: families, very high education, high income, managers/professionals, technical/ sales

4. Cluster 16 Country Home Families: large families, rural areas, medium education, medium income, precision/crafts

5. Cluster 8 Movers and Shakers: singles, couples, students and recent graduates, high education and income, managers/professionals, technical/sales

6. Cluster 15 Great Beginnings: young, singles and couples, medium-high education, medium income, some renters, managers/professionals, technical/sales