我想知道如何在下面回圈我的代碼以使其更具功能性和可推廣到其他資料（當前資料只是一個玩具）：
FIRST，我study從datausing 中選擇一個sample()，然后選擇filter()它的行outcome == outcome_to_remove。這給出了datat輸出。
SECOND，我study從datatusing 中選擇一個sample()，然后選擇filter()它的行outcome == outcome_to_remove2。這給出了最終的輸出。
我們可以回圈這個程序嗎？
編輯：我想添加到我的代碼中的唯一條件是length(unique(data$study))回圈之前和之后應該始終保持不變。也就是說，a 應該不可能在步驟中study丟失，并且在步驟中，因此整個研究被洗掉。outcome == "A"FIRSToutcome == "B"SECOND
(data <- expand_grid(study = 1:5, group = 1:2, outcome = c("A", "B")))
n = 1
#====-------------------- FIRST:
studies_to_remove = sample(unique(data$study), size = n)
outcome_to_remove = c("A")
datat <- data %>%
filter(
!( study %in% studies_to_remove &
outcome %in% outcome_to_remove
))
#====------------------- SECOND:
studies_to_remove2 = sample(unique(datat$study), size = n)
outcome_to_remove2 = c("B")
datat %>%
filter(
!( study %in% studies_to_remove2 &
outcome %in% outcome_to_remove2
))
uj5u.com熱心網友回復：
在for回圈的幫助下-
data <- tidyr::expand_grid(study = 1:5, group = 1:2, outcome = c("A", "B"))
n = 1
set.seed(9873)
outcome_to_remove <- unique(data$outcome)
unique_study <- unique(data$study)
for(i in outcome_to_remove) {
studies_to_remove = sample(unique_study, size = n)
outcome_to_remove = i
unique_study <- setdiff(unique_study, studies_to_remove)
cat('\nDropping study ', studies_to_remove, 'and outcome ', outcome_to_remove)
data <- data %>%
filter(
!( study %in% studies_to_remove &
outcome %in% outcome_to_remove
))
}
#Dropping study 3 and outcome A
#Dropping study 1 and outcome B
data
# study group outcome
# <int> <int> <chr>
# 1 1 1 A
# 2 1 2 A
# 3 2 1 A
# 4 2 1 B
# 5 2 2 A
# 6 2 2 B
# 7 3 1 B
# 8 3 2 B
# 9 4 1 A
#10 4 1 B
#11 4 2 A
#12 4 2 B
#13 5 1 A
#14 5 1 B
#15 5 2 A
#16 5 2 B
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