回答編集履歴
2
test
CHANGED
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@@ -10,12 +10,11 @@
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c("無治療", NA, "A", NA, NA)))
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#
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lst <- c("中断", "無治療", "無治療")
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names(
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next_tyra <- setNames(c("中断", "無治療", "無治療"), c("A", "中断", "無治療"))
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data2 <- data %>%
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group_by(id) %>%
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mutate(
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tyra = accumulate(tyra, ~ifelse(is.na(.y),
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tyra = accumulate(tyra, ~ifelse(is.na(.y), next_tyra[last(.x)], .y))
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) %>%
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ungroup()
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1
test
CHANGED
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@@ -1,5 +1,4 @@
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1
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以下は `t
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以下は `purrr::accumulate()` を利用する場合です。
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2
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-
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3
2
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```r
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library(tidyverse)
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4
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@@ -10,27 +9,35 @@
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c("無治療", NA, NA, "A", "A"),
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c("無治療", NA, "A", NA, NA)))
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data_out <- data.frame(
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id = c(rep(1, 5), rep(2, 5), rep(3, 5)),
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phase = c(rep(1:5,3)),
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tyra = c(c("A", "A", "A", "中断", "無治療"),
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c("無治療", "無治療", "無治療", "A", "A"),
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c("無治療", "無治療", "A", "中断", "無治療")))
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-
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#
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lst <- c("中断", "無治療", "無治療")
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names(lst) <- c("A", "中断", "無治療")
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data2 <- data %>%
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group_by(id) %>%
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-
mutate(across(tyra, ~{
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-
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mutate(
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-
for (i in .x) {
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-
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tyra = accumulate(tyra, ~ifelse(is.na(.y), lst[last(.x)], .y))
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}
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v
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-
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) %>%
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ungroup()
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data2
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# # A tibble: 15 × 3
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# id phase tyra
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# <dbl> <int> <chr>
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# 1 1 1 A
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# 2 1 2 A
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# 3 1 3 A
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# 4 1 4 中断
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# 5 1 5 無治療
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# 6 2 1 無治療
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# 7 2 2 無治療
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# 8 2 3 無治療
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# 9 2 4 A
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# 10 2 5 A
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# 11 3 1 無治療
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# 12 3 2 無治療
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# 13 3 3 A
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# 14 3 4 中断
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# 15 3 5 無治療
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```
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