A sampling of all products purchased by households within the Complete Journey study. Each line found in this table is essentially the same line that would be found on a store receipt. This is only a subsample of the complete data set to keep package size manageable.
transactions_sample
A data frame with 75,000 rows and 11 variables
Uniquely identifies each household
Uniquely identifies each store
Uniquely identifies a purchase occasion
Uniquely identifies each product
Number of the products purchased during the trip
Amount of dollars retailer receives from sale
Discount applied due to retailer's loyalty card program
Discount applied due to manufacturer coupon
Discount applied due to retailer's match of manufacturer coupon
Week of the transaction; Ranges 1-53
Date and time of when the transaction occurred
84.51°, Customer Journey study, http://www.8451.com/area51/
a tibble
Use get_transactions to download the entire transactions
data containing all 1,469,307 rows.
transactions_sample#> # A tibble: 75,000 x 11 #> household_id store_id basket_id product_id quantity sales_value retail_disc #> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> #> 1 2261 309 31625220… 940996 1 3.86 0.43 #> 2 2131 368 32053127… 873902 1 1.59 0.9 #> 3 511 316 32445856… 847901 1 1 0.69 #> 4 400 388 31932241… 13094913 2 11.9 2.9 #> 5 918 340 32074655… 1085604 1 1.29 0 #> 6 718 324 32614612… 883203 1 2.5 0.49 #> 7 868 323 32074722… 9884484 1 3.49 0 #> 8 1688 450 34850403… 1028715 1 2 1.79 #> 9 467 31782 31280745… 896613 2 6.55 4.44 #> 10 1947 32004 32744181… 978497 1 3.99 0 #> # … with 74,990 more rows, and 4 more variables: coupon_disc <dbl>, #> # coupon_match_disc <dbl>, week <int>, transaction_timestamp <dttm>