如何在 R 中合并此数据集？答案

【问题标题】：How can I coalesce this dataset in R?如何在 R 中合并此数据集？
【发布时间】：2021-11-09 20:31:09
【问题描述】：

我是一名 ICU 医生，从事的研究涉及从 ICU 计算机系统中获取大量与患者相关的数据（所有这些数据都经过伦理批准等）。通常情况下，取出数据需要清理和整理才能正确使用。

我已经获得了一组数据，并尽我所能对其进行了争论。当然，我的数据科学技能还很初级，尽管我是一个热心的 R 用户，但我完全陷入了困境，希望你们中的一些人能够阐明我的问题以及如何解决它。我绝对无法解决这个问题，但怀疑这是时间序列工作中经常遇到的问题。

目前，我的数据集现在包含每个时间点的多行。因此，在时间 X 有一个单独的行用于心率、血压等。有 46 个观察值，并且每个时间点都重复（该患者总共 344 个）。并非在每个时间点记录所有观察结果。我提供了此数据排列方式的屏幕截图链接here。

数据样本是here，有帮助吗？

我取得的最大进展是使用以下嵌套的 for 循环结构。它适用于第一组观察。我尝试了一种奇怪的 while 循环安排，但结果却是一头雾水。

# First, add a group to the entire table specifying each time point that 
# observations were conducted. 
Patient_full$Verification_group <- as.numeric(as.factor(Patient_full$Time))

# Get the number of these groups
observation_times <- max(Patient_full$Verification_group)

# Create the bare bones of an overall table. This is the first row of the table.
patient_obs_final <-  Patient_full[1,]

# Next I need to create a loop within loop. The master loop will coerce rows
# that have been created by the sub-loop.
for (i in 1 : observation_times) {
  
  # Isolate the overall observation group you are dealing with
  veri_group <- filter(Patient_full, Verification_group == i)

  # Start by getting some numbers to run the sub-loop
  lowest_obs_time_row <- min(veri_group$Row)
  highest_obs_time_row <- max(veri_group$Row)
  rows_in_obs_time <- (highest_obs_time_row - lowest_obs_time_row)
  
  # We can run the sub-loop now
  obs_at_timepoint <- Patient_full[lowest_obs_time_row, ]
  for (j in 1 : (rows_in_obs_time - 1)) {
    obs_at_timepoint <- coalesce(obs_at_timepoint, Patient_full[j + 1,])
    
  }
  
  patient_obs_final <-  rbind(patient_obs_final, obs_at_timepoint)
  
}

patient_obs_final

一旦 j 变为 2，事情似乎就崩溃了。

所以，最终我的目标是为每个时间点设置一个单独的行，并让该行包含当时记录/观察到的任何内容。我不知所措，甚至无法说出为什么我的解决方案不起作用。任何建议将不胜感激。

【问题讨论】：

欢迎。通常，如果您将dput(dat) 的输出粘贴到您的问题中，其他人可以更轻松地回答您的问题，以便人们可以重现您的数据。

标签： r dataframe coalesce

【解决方案1】：

不要循环执行。一个summarise_at就够了！！

library(tidyverse)
Patient_01_sample <- read.csv("E:/R/StackOverflow/Patient_01_sample.xlsx - Sheet 1.csv", row.names=1)
f = function(x) ifelse(length(x[!is.na(x)])==0,NA,x[!is.na(x)][1]) 
Patient = read_csv("Patient_01_sample.xlsx - Sheet 1.csv")
Patient %>% group_by(Time) %>% 
  summarise_at(vars(3:45), f)

输出

# A tibble: 5 x 44
  Time                `Glucose ABG` `Lactate ABG` PaCO2  PaO2 `PH (ABG)` `Potassium ABG` `Sodium ABG` `Cardiac Rhythm` `Arterial Pressure Di~
  <dttm>                      <dbl>         <dbl> <dbl> <dbl>      <dbl>           <dbl>        <dbl> <chr>                             <dbl>
1 2017-09-04 17:00:00          11.8          10.7  4.42  31.5       7.25             3.9          3.9 ST                                   NA
2 2017-09-04 17:55:00          NA            NA   NA     NA        NA               NA           NA   NA                                   54
3 2017-09-04 18:00:00          NA            NA   NA     NA        NA               NA           NA   ST                                   60
4 2017-09-04 19:00:00          10.1           9.7  4.22  15         7.3              3.9          3.9 ST                                   58
5 2017-09-04 20:00:00           8.1           7.2  5.07  16.9       7.27             3.9          3.9 ST                                   62
# ... with 34 more variables: Arterial Pressure Mean <dbl>, Arterial Pressure Systolic <dbl>, Heart Rate <dbl>,
#   Non Invasive Arterial Pressure Diastolic <dbl>, Non Invasive Arterial Pressure Mean <dbl>,
#   Non Invasive Arterial Pressure Systolic <dbl>, Tympanic Temperature <dbl>, Patient Positioning ABG <lgl>, Central Venous Pressure <lgl>,
#   Delivered Percent O2 <lgl>, Mean Airway Pressure S <lgl>, Minute Volume expired (S) <lgl>, Peak Inspiratory Pressure measured  S <lgl>,
#   Positive End Expiratory pressure <lgl>, S Expired Tidal vol. (breath) <lgl>, S Tidal Volume Inspired <lgl>, Servo i Modes <lgl>,
#   Set FiO2 <lgl>, Set Flow Trigger S <lgl>, Set Pause time % <lgl>, Set PEEP Servo <lgl>, Set rate (CMV or SIMV) <lgl>,
#   Set Tidal Volume (servo) <lgl>, Set Upper Pressure Limit <lgl>, Spontaneous Rate  S <lgl>, Cardiac output (Vigileo) <lgl>, ...

【讨论】：

【解决方案2】：

正如@r2evans 所指出的，此校准也可以使用dplyr::pivot_wider 完成。正如他所建议的，我们需要一个小技巧，即将所有列转换为字符，然后在用pivot_wider改回宽后回到原来的类。

library(readxl)
library(dplyr)

df<-read.xlsx("Patient_01_sample.xlsx")

df %>% mutate(`Cardiac Rhythm`=replace(`Cardiac Rhythm`, `Cardiac Rhythm`=='', NA)) %>%
        select(-1) %>%
        mutate(across(-1, as.character)) %>%
        pivot_longer(-1)%>%
        group_by(name) %>%
        filter(!is.na(value)) %>%
        ungroup%>%
        pivot_wider(id_cols=Time) %>%
        mutate(across(-c(1, `Cardiac Rhythm`), as.numeric))

# A tibble: 5 x 18
  Time                `Base excess (vt)` `Glucose ABG` `Lactate ABG` PaCO2  PaO2 `PH (ABG)` `Potassium ABG`
  <dttm>                           <dbl>         <dbl>         <dbl> <dbl> <dbl>      <dbl>           <dbl>
1 2017-09-04 17:00:00              -11.4          11.8          10.7  4.42  31.5       7.25             3.9
2 2017-09-04 17:55:00               NA            NA            NA   NA     NA        NA               NA  
3 2017-09-04 18:00:00               NA            NA            NA   NA     NA        NA               NA  
4 2017-09-04 19:00:00               -9.3          10.1           9.7  4.22  15         7.3              3.9
5 2017-09-04 20:00:00               -8.4           8.1           7.2  5.07  16.9       7.27             3.9
# … with 10 more variables: Sodium ABG <dbl>, Cardiac Rhythm <chr>, Arterial Pressure Diastolic <dbl>,
#   Arterial Pressure Mean <dbl>, Arterial Pressure Systolic <dbl>, Heart Rate <dbl>,
#   Non Invasive Arterial Pressure Diastolic <dbl>, Non Invasive Arterial Pressure Mean <dbl>,
#   Non Invasive Arterial Pressure Systolic <dbl>, Tympanic Temperature <dbl>

【讨论】：

【解决方案3】：

试试这个dplyr 解决方案：

library(dplyr)
dat %>%
  group_by(Time) %>%
  mutate(
    Cardiac.Rhythm = if_else(nzchar(Cardiac.Rhythm), Cardiac.Rhythm, NA_character_), 
    across(-Row, ~ .[order(is.na(.))])
  ) %>%
  ungroup() %>%
  filter(rowSums(!is.na(.)) > 2) %>%
  as.data.frame()
#   Row                Time Base.excess..vt. Glucose.ABG Lactate.ABG PaCO2 PaO2 PH..ABG. Potassium.ABG Sodium.ABG Cardiac.Rhythm Arterial.Pressure.Diastolic Arterial.Pressure.Mean Arterial.Pressure.Systolic Heart.Rate
# 1   1 2017-09-04 17:00:00            -11.4        11.8        10.7  4.42 31.5     7.25           3.9        3.9             ST                          NA                     NA                         NA         NA
# 2  10 2017-09-04 17:55:00               NA          NA          NA    NA   NA       NA            NA         NA           <NA>                          54                     68                         92        123
# 3  14 2017-09-04 18:00:00               NA          NA          NA    NA   NA       NA            NA         NA             ST                          60                     71                         86        123
# 4  23 2017-09-04 19:00:00             -9.3        10.1         9.7  4.22 15.0     7.30           3.9        3.9             ST                          58                     70                         92        122
# 5  36 2017-09-04 20:00:00             -8.4         8.1         7.2  5.07 16.9     7.27           3.9        3.9             ST                          62                     80                        117         NA

（我截断了粘贴在这里的列...）

演练：

由于某种原因，Cardiac.Rhythm 有空字符串而不是 NA，第一个 mutate 将空字符串 "" 转换为 NA，以便后面的过滤起作用；
.[order(is.na(.))] 在每列中将非NA 数据排在首位；
rowSums(.) 确保我们在一行中至少有一个非NA 数据（> 2 考虑到Row 和Time 不是NA）。

注意事项：

我假设数据是每帧一个“人”；如果您的数据中有患者 ID，请务必将其添加到 group_by(.) 中。
在特定的Time（和Patient_ID，如果存在）中，我假设行的顺序并不重要（因此每列重新排序值）。
我确实不假设每一列每个Time 只能有一个值；虽然从逻辑上讲这种情况是有道理的，但在此之前的数据抓取/聚合中也可能存在错误，所以我故意不假设x[!is.na(x)]（按Time分组时）总是会返回长度 1。这将作为特定 Time 中的两行（或更多行）。
我考虑过为此使用pivot_longer，但它仍然可能，但是......你这里有numeric和character数据，所以整理出来有点问题好吧。

数据

dat <- structure(list(Row = 1:47, Time = c("2017-09-04 17:00:00", "2017-09-04 17:00:00", "2017-09-04 17:00:00", "2017-09-04 17:00:00", "2017-09-04 17:00:00", "2017-09-04 17:00:00", "2017-09-04 17:00:00", "2017-09-04 17:00:00", "2017-09-04 17:00:00", "2017-09-04 17:55:00", "2017-09-04 17:55:00", "2017-09-04 17:55:00", "2017-09-04 17:55:00", "2017-09-04 18:00:00", "2017-09-04 18:00:00", "2017-09-04 18:00:00", "2017-09-04 18:00:00", "2017-09-04 18:00:00", "2017-09-04 18:00:00", "2017-09-04 18:00:00", "2017-09-04 18:00:00", "2017-09-04 18:00:00", "2017-09-04 19:00:00", "2017-09-04 19:00:00", "2017-09-04 19:00:00", "2017-09-04 19:00:00", "2017-09-04 19:00:00", "2017-09-04 19:00:00", "2017-09-04 19:00:00", "2017-09-04 19:00:00", "2017-09-04 19:00:00", "2017-09-04 19:00:00", "2017-09-04 19:00:00", "2017-09-04 19:00:00", "2017-09-04 19:00:00", "2017-09-04 20:00:00", "2017-09-04 20:00:00", "2017-09-04 20:00:00", "2017-09-04 20:00:00", "2017-09-04 20:00:00", "2017-09-04 20:00:00", "2017-09-04 20:00:00", "2017-09-04 20:00:00", "2017-09-04 20:00:00", "2017-09-04 20:00:00", "2017-09-04 20:00:00", "2017-09-04 20:00:00" ), Base.excess..vt. = c(-11.4, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, -9.3, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, -8.4, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Glucose.ABG = c(NA, 11.8, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 10.1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 8.1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Lactate.ABG = c(NA, NA, 10.7, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 9.7, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 7.2, NA, NA, NA, NA, NA, NA, NA, NA, NA), PaCO2 = c(NA, NA, NA, 4.42, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 4.22, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 5.07, NA, NA, NA, NA, NA, NA, NA, NA), PaO2 = c(NA, NA, NA, NA, 31.5, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 15, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 16.9, NA, NA, NA, NA, NA, NA, NA), PH..ABG. = c(NA, NA, NA, NA, NA, 7.25, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 7.3, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 7.27, NA, NA, NA, NA, NA, NA), Potassium.ABG = c(NA, NA, NA, NA, NA, NA, 3.9, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 3.9, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 3.9, NA, NA, NA, NA, NA), Sodium.ABG = c(NA, NA, NA, NA, NA, NA, 3.9, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 3.9, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 3.9, NA, NA, NA, NA, NA), Cardiac.Rhythm = c("", "", "", "", "", "", "", "", "ST", "", "", "", "", "", "", "", "ST", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "ST", "", "", "", "", "", "", "", "", "", "", "", "", "ST"), Arterial.Pressure.Diastolic = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, 54L, NA, NA, NA, 60L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 58L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 62L, NA, NA, NA), Arterial.Pressure.Mean = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 68L, NA, NA, NA, 71L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 70L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 80L, NA, NA), Arterial.Pressure.Systolic = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 92L, NA, NA, NA, 86L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 92L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 117L, NA ), Heart.Rate = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 123L, NA, NA, NA, NA, 123L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 122L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Non.Invasive.Arterial.Pressure.Diastolic = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 58L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Non.Invasive.Arterial.Pressure.Mean = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 71L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Non.Invasive.Arterial.Pressure.Systolic = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 108L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Tympanic.Temperature = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 37.6, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Patient.Positioning.ABG = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Central.Venous.Pressure = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Delivered.Percent.O2 = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Mean.Airway.Pressure.S = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Minute.Volume.expired..S. = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Peak.Inspiratory.Pressure.measured..S = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Positive.End.Expiratory.pressure = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), S.Expired.Tidal.vol...breath. = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), S.Tidal.Volume.Inspired = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Servo.i.Modes = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Set.FiO2 = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Set.Flow.Trigger.S = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA ), Set.Pause.time.. = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Set.PEEP.Servo = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA ), Set.rate..CMV.or.SIMV. = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Set.Tidal.Volume..servo. = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Set.Upper.Pressure.Limit = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Spontaneous.Rate..S = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Cardiac.output..Vigileo. = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), DO2.Vigileo. = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), DO2I.Vigileo. = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Stroke.Volume.Index.Vigileo. = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Stroke.Volume.Vigileo. = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Systemic.Vascular.Resistance.Index.Vigileo. = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Systemic.Vascular.Resistance.Vigileo. = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Ionised.Calcium.ABG = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Set.Pressure.Control.level.above.PEEP.S. = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA)), class = "data.frame", row.names = c(NA, -47L))

【讨论】：

感谢您的回答。老实说，你这样做的方式超出了我的理解，我还不能具体实施。我会继续努力的！
奇怪的是它导致了问题，这是在您宣传的数据集上完成的，没有错误/警告，并产生了这 5 行结果数据。
哦，我相信你，问题出在我身上。我相信我在一个非常基本的水平上运作，当我看到你所做的事情时，我并没有点击它。在数据争论方面，尽管我很想把它做好，但我仍然在操作一个非常基础的水平！
我能问一个非常简单的问题吗？您使用什么工具读取我的数据？
我去了你的链接，然后突出显示数据并复制，然后在我的 R 中运行类似read.delim(text = paste(readClipboard(), collapse = "\r\n"), as.is=TRUE, header=TRUE) 的东西（给予或接受，我有一个帮助函数为我完成大部分工作）。