R 中的 for 循环：如何应用定义的函数循环遍历 R 中的行和列？

Question

我有一个名为 trainset 的数据集，它有 50 个变量。对于每一行，我需要汇总名为 Systolic.Blood.Pressure、Blood.Urea.Nitrogen、Blood.Sodium、年龄、heart.rR 和 COPD 值的列下的值。我已经定义了一个函数来总结这些：

m.gwtg = function(Systolic.BP, Sodium, COPD){
  if (Systolic.BP>=200){
    pt.sbp = 0
  }else if (Systolic.BP>= 190){
    pt.sbp = 2
  }else if (Systolic.BP>= 180){
    pt.sbp = 4
  }else if (Systolic.BP>= 170){
    pt.sbp = 6
  }else if (Systolic.BP>= 160){
    pt.sbp = 8
  }else if (Systolic.BP>= 150){
    pt.sbp = 9
  }else if (Systolic.BP>= 140){
  if (Sodium>=139){
    pt.sodium =  0
  }else if (Sodium>= 137){
    pt.sodium =  1
  }else if (Sodium>= 134){
    pt.sodium =  2
  }
  if (Age>=110){
    pt.age = 28
  }else if (Age>= 100){
    pt.age = 25
  }else if (Age>= 90){
    pt.age = 22
  }else if (Age>= 80){
    pt.age = 19
  }else if (Age>= 70){
  if (COPD == 1){
    pt.copd =2
  } else {
    pt.copd = 0
  }
  total = pt.sbp + pt.bun+ pt.sodium +pt.age + pt.hr+ pt.copd
  return(if (total < 79){
    outcome = 0
  } else {
    outcome = 1
  })
}

我在编写 for 循环以循环遍历训练集并应用为每一行定义的函数时遇到问题。我试着像这样编写循环代码：

for (i in 1:nrow(trainset)) {
  Systolic.BP[i] <- trainset$Systolic.blood.pressure[i]
  Sodium[i]  <- trainset$Blood.sodium[i]
  COPD[i]  <- trainset$COPD[i]
  total[i] <- Systolic.BP[i]+ Sodium[i] +COPD[i]
  
  outcome.gwtg.trainset[i]= m.gwtg(total[i])
  
}

我对 for 循环的代码感到很困惑。感谢您的任何回答！

Answer 1

这是一种更简洁的计算结果的方法：

library(tidyverse)

calc_score <- function(systolic_bp, bun, sodium) {
  systolic_bp_score <- case_when(
    systolic_bp >= 200 ~ 0,
    systolic_bp >= 190 ~ 2,
    systolic_bp >= 180 ~ 4
  )
  bun_score <- case_when(
    bun >= 150 ~ 28,
    bun >= 140 ~ 27
  )
  sodium_score <- case_when(
    sodium >= 139 ~ 0,
    sodium >= 137 ~ 1
  )
  systolic_bp_score + bun_score + sodium_score
}

# example data
trainset <- tibble(
  systolic_bp = c(180, 195),
  bun = c(145, 180),
  sodium = c(138, 140)
)

trainset %>%
  mutate(
    score = list(systolic_bp, bun, sodium) %>% pmap_dbl(calc_score),
    outcome = as.numeric(score > 97)
  )
#> # A tibble: 2 × 5
#>   systolic_bp   bun sodium score outcome
#>         <dbl> <dbl>  <dbl> <dbl>   <dbl>
#> 1         180   145    138    32       0
#> 2         195   180    140    30       0

^{由 reprex package (v2.0.0)}

创建于 2022-03-25

Answer 2

您应该尽可能避免在 R 中使用循环和类似函数（例如，*apply() 和 purrr::map()）。R 设计为使用向量，循环要慢得多。

代替此循环操作，执行以下操作：

将每一列重新编码为其转换后的值
将转换后的值相加
将转换后的值重新编码为 0/1 结果

应该完成这些操作 vector-wise 以提高效率（并避免您遇到的棘手的索引问题）。

例如：

m.gwtg <- function(data) {
  data <- dplyr::mutate(data, 
    pt.sbp = dplyr::case_when(
      Systolic.BP >= 200 ~ 0,
      Systolic.BP >= 190 ~ 2,
      Systolic.BP >= 180 ~ 4,
      Systolic.BP >= 170 ~ 6,
      Systolic.BP >= 160 ~ 8,
      Systolic.BP >= 150 ~ 9,
      Systolic.BP >= 140 ~ 11,
      Systolic.BP >= 130 ~ 13,
      Systolic.BP >= 120 ~ 15,
      Systolic.BP >= 110 ~ 17,
      Systolic.BP >= 100 ~ 19,
      Systolic.BP >=  90 ~ 21,
      Systolic.BP >=  80 ~ 23,
      Systolic.BP >=  70 ~ 24,
      Systolic.BP >=  60 ~ 26,
      Systolic.BP >=  50 ~ 28, # should Systolic.BP < 50 be NA or 28?
      # else
      TRUE ~ NA_real_
    ),
    pt.bun = dplyr::case_when(
      BUN >= 150 ~ 28,
      BUN >= 140 ~ 27,
      BUN >= 130 ~ 25,
      BUN >= 120 ~ 23,
      BUN >= 110 ~ 21,
      BUN >= 100 ~ 19,
      BUN >=  90 ~ 17,
      BUN >=  80 ~ 15,
      BUN >=  70 ~ 13,
      BUN >=  60 ~ 11,
      BUN >=  50 ~  9,
      BUN >=  40 ~  8,
      BUN >=  30 ~  6,
      BUN >=  20 ~  4,
      BUN >=  10 ~  2,
      BUN  <  10 ~  0,
      # else
      TRUE ~ NA_real_
    ),
    pt.sodium = dplyr::case_when(
      Sodium >= 139 ~ 0,
      Sodium >= 137 ~ 1,
      Sodium >= 134 ~ 2,
      Sodium >= 131 ~ 3,
      Sodium  < 131 ~ 4,
      # else
      TRUE ~ NA_real_
    ),
    pt.age = dplyr::case_when(
      Age >= 110 ~ 28,
      Age >= 100 ~ 25,
      Age >=  90 ~ 22,
      Age >=  80 ~ 19,
      Age <=  70 ~ 17,
      Age >=  60 ~ 14,
      Age >=  50 ~ 11,
      Age <=  40 ~  8,
      Age >=  30 ~  6,
      Age >=  20 ~  3,
      Age  <  20 ~  0,
      # else
      TRUE ~ NA_real_
    ),
    pt.hr = dplyr::case_when(
      HR >= 105 ~ 8,
      HR >= 100 ~ 6,
      HR >=  95 ~ 5,
      HR >=  90 ~ 4,
      HR >=  85 ~ 3,
      HR >=  80 ~ 1,
      HR  <  80 ~ 0,
      # else
      TRUE ~ NA_real_
    ),
    pt.copd = dplyr::case_when(
      COPD == 1 ~ 2,
      COPD == 0 ~ 0,
      # else
      TRUE ~ NA_real_
    ),
    total = pt.sbp + pt.bun + pt.sodium + pt.age + pt.hr + pt.copd,
    outcome = dplyr::if_else(total < 79, 0, 1)
  )
  return(data)
}

example_data <- data.frame(
  Systolic.BP = c(170, 160, 200), 
  BUN = c(60, 150, 10), 
  Sodium = c(134, 131, 139), 
  Age = c(40, 80, 20), 
  HR = c(90, 105, 80), 
  COPD = c(1, 0, 0)
)

m.gwtg(example_data)
#>   Systolic.BP BUN Sodium Age  HR COPD pt.sbp pt.bun pt.sodium pt.age pt.hr
#> 1         170  60    134  40  90    1      6     11         2     17     4
#> 2         160 150    131  80 105    0      8     28         3     19     8
#> 3         200  10    139  20  80    0      0      2         0     17     1
#>   pt.copd total outcome
#> 1       2    42       0
#> 2       0    66       0
#> 3       0    20       0

^{由 reprex package (v2.0.1)}

于 2022-03-25 创建

R 中的 for 循环：如何应用定义的函数循环遍历 R 中的行和列？

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