library(data.table) library(magrittr) # fake data; 1000 rows set.seed(1234) d0 <- data.table( item_id = 1L:1000L, ttl = runif(1000L), item_category_id = sample(1L:83L, 1000L, replace = T) ) d1 <- d0[, .( sum.of.ttl.by.item_category_id = sum(ttl), raw.of.item = list(item_id), raw.of.ttl = list(ttl) ), by = .(item_category_id)] head(d1) # item_category_id sum.of.ttl.by.item_category_id raw.of.item # 1: 75 9.775620 1, 86,113,278,309,377,... # 2: 64 8.876390 2, 28, 39, 41,172,269,... # 3: 66 5.105777 3,170,195,211,230,233,... # 4: 24 7.403771 4, 12, 57,101,183,267,... # 5: 57 6.665990 5, 37, 73,191,259,360,... # 6: 31 4.670723 6, 22,452,473,549,603,... # raw.of.ttl # 1: 0.1137034,0.8985805,0.9503049,0.5447566,0.5484554,0.7593397,... # 2: 0.62229940,0.91465817,0.99215042,0.55333359,0.58427152,0.04946115,... # 3: 0.6092747,0.3252783,0.8100834,0.5663108,0.4944386,0.1066968,... # 4: 0.62337944,0.54497484,0.49396092,0.03545673,0.60071414,0.74816114,... # 5: 0.86091538,0.20124804,0.01462726,0.63891131,0.58951654,0.76815200,... # 6: 0.6403106053,0.3026933707,0.7759688012,0.0006121558,0.9797886356,0.1702244373,... d1$raw.of.item[1:2] # [[1]] # [1] 1 86 113 278 309 377 426 457 493 505 569 627 643 798 840 980 995 # # [[2]] # [1] 2 28 39 41 172 269 286 311 431 579 668 702 768 782 828 908 942 d1$raw.of.ttl[1:2] # [[1]] # [1] 0.1137034 0.8985805 0.9503049 0.5447566 0.5484554 0.7593397 0.1999333 0.2468865 0.9126530 0.6744341 0.2085592 0.4840459 # [13] 0.5096489 0.8223393 0.6235133 0.5847833 0.6936828 # # [[2]] # [1] 0.62229940 0.91465817 0.99215042 0.55333359 0.58427152 0.04946115 0.28077262 0.91342167 0.66349054 0.55109725 0.28465309 # [12] 0.59863873 0.57321496 0.05653095 0.39876005 0.25607750 0.58355793