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_sampleA 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.
# \donttest{
transactions_sample
#> # A tibble: 75,000 × 11
#> household_id store_id basket_id product_id quantity sales_value retail_disc
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl>
#> 1 2261 309 31625220889 940996 1 3.86 0.43
#> 2 2131 368 32053127496 873902 1 1.59 0.9
#> 3 511 316 32445856036 847901 1 1 0.69
#> 4 400 388 31932241118 13094913 2 11.9 2.9
#> 5 918 340 32074655895 1085604 1 1.29 0
#> 6 718 324 32614612029 883203 1 2.5 0.49
#> 7 868 323 32074722463 9884484 1 3.49 0
#> 8 1688 450 34850403304 1028715 1 2 1.79
#> 9 467 31782 31280745102 896613 2 6.55 4.44
#> 10 1947 32004 32744181707 978497 1 3.99 0
#> # ℹ 74,990 more rows
#> # ℹ 4 more variables: coupon_disc <dbl>, coupon_match_disc <dbl>, week <int>,
#> # transaction_timestamp <dttm>
# }