嵌套if / else条件在多列值上-R

Question

目的是根据多个条件填充一个新列(df$final.count)。下面是一个示例数据框架：

structure(list(item = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 
2L, 2L, 2L), .Label = c("a", "b"), class = "factor"), raw.count = c(16, 
300, 203, 6, 5, 40, 20, 16, 300, 203), loc = structure(c(4L, 
2L, 2L, 2L, 2L, 3L, 3L, 4L, 2L, 3L), .Label = c("  ", "in", "out", 
"NA"), class = "factor"), side = structure(c(4L, 2L, 3L, 2L, 
3L, 4L, 3L, 4L, 2L, 4L), .Label = c("F", "L", "R", "NA"), class = "factor"), 
    recount = c(15, NA, NA, 7, NA, NA, 16, 15, NA, NA), final.count = c(NA_real_, 
    NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
    NA_real_, NA_real_, NA_real_), EXPECTED = c(15, 60, 120, 
    7, 5, 40, 16, 15, 300, 203)), row.names = c(NA, 10L), class = "data.frame")

目标是根据影响多列的下列条件填充一个新列(df$final.count)：

1. 如果df$recount中有比df$recount更多的数字，则在df$final.count中应该无条件地使用其他列值。
2. 如果df$recount中没有数字(NA)，且df$raw.count > 10，df$loc是in，df$side是"L“，则应使用函数0.2*df$raw.count填充df$final.count。
3. 如果df$recount中没有数字(NA)，并且df$raw.count > 10，df$loc是in，df$side是"R“，则函数0.6*df$raw.count应该用来填充df$final.count (注意，只有侧不同)。
4. 如果应该使用df$raw.count =<10而不是df$raw.count，那么如果上面的1
5. 如果df$loc是"out“而不是df$final.count <- df$raw.count，则无条件地对其他列值进行删除，如果上面的1仍然有效

我已经在循环中尝试过各种if / else的版本，例如：

  for (i in 1:nrow(df)) {
  if(!is.na(df$recount[i]) {
    df$final.count <- df$recount
  }
  else if(df$item[i] == "a" & df$raw.count[i] > 10 & df$loc[i] == "in" & df$side[i] == "L") {
    df$final.count <- 0.2*df$raw.count[i]
  }
  else if(df$item[i] == "a" & df$raw.count[i] > 10 & df$loc[i] == "in" & df$side[i] == "R") {
    df$final.count <- 0.6*df$raw.count[i]
  }
  else if(df$raw.count <= 10){
    df$final.count <- df$raw.count
  }
  else(df$loc == "out") {
    df$final.count <- df$raw.count
  }
}

Answer 1

如果您使用来自dplyr包的case_when()，它将变得更加可读性。您也可以松掉for。

library( dplyr )
df %>%
  mutate( final.cond = case_when(
    !is.na( recount ) ~ recount,
    item == "a" & raw.count > 10 & loc == "in" & side == "L" ~ 0.2 * raw.count,
    item == "a" & raw.count > 10 & loc == "in" & side == "R" ~ 0.6 * raw.count,
    raw.count <= 10 ~ raw.count,
    loc == "out" ~ raw.count,
    TRUE ~ as.numeric(NA)
  ))