Orange Juice Data#

The data contains 1070 purchases where the customer either purchased Citrus Hill or Minute Maid Orange Juice. A number of characteristics of the customer and product are recorded.

  • Purchase: A factor with levels ‘CH’ and ‘MM’ indicating whether the customer purchased Citrus Hill or Minute Maid Orange Juice

  • WeekofPurchase: Week of purchase

  • StoreID: Store ID

  • PriceCH: Price charged for CH

  • PriceMM: Price charged for MM

  • DiscCH: Discount offered for CH

  • DiscMM: Discount offered for MM

  • SpecialCH: Indicator of special on CH

  • SpecialMM: Indicator of special on MM

  • LoyalCH: Customer brand loyalty for CH

  • SalePriceMM: Sale price for MM

  • SalePriceCH: Sale price for CH

  • PriceDiff: Sale price of MM less sale price of CH

  • Store7: A factor with levels ‘No’ and ‘Yes’ indicating whether the sale is at Store 7

  • PctDiscMM: Percentage discount for MM

  • PctDiscCH: Percentage discount for CH

  • ListPriceDiff: List price of MM less list price of CH

  • STORE: Which of 5 possible stores the sale occured at

Source#

Stine, Robert A., Foster, Dean P., Waterman, Richard P. Business Analysis Using Regression (1998). Published by Springer.

from ISLP import load_data
OJ = load_data('OJ')
OJ.columns

Index(['Purchase', 'WeekofPurchase', 'StoreID', 'PriceCH', 'PriceMM', 'DiscCH',
       'DiscMM', 'SpecialCH', 'SpecialMM', 'LoyalCH', 'SalePriceMM',
       'SalePriceCH', 'PriceDiff', 'Store7', 'PctDiscMM', 'PctDiscCH',
       'ListPriceDiff', 'STORE'],
      dtype='object')

OJ.shape

(1070, 18)

OJ.columns

Index(['Purchase', 'WeekofPurchase', 'StoreID', 'PriceCH', 'PriceMM', 'DiscCH',
       'DiscMM', 'SpecialCH', 'SpecialMM', 'LoyalCH', 'SalePriceMM',
       'SalePriceCH', 'PriceDiff', 'Store7', 'PctDiscMM', 'PctDiscCH',
       'ListPriceDiff', 'STORE'],
      dtype='object')

OJ.describe().iloc[:,:4]
WeekofPurchase StoreID PriceCH PriceMM
count 1070.000000 1070.000000 1070.000000 1070.000000
mean 254.381308 3.959813 1.867421 2.085411
std 15.558286 2.308984 0.101970 0.134386
min 227.000000 1.000000 1.690000 1.690000
25% 240.000000 2.000000 1.790000 1.990000
50% 257.000000 3.000000 1.860000 2.090000
75% 268.000000 7.000000 1.990000 2.180000
max 278.000000 7.000000 2.090000 2.290000