如何在 R 中删除包含特定字符串的行？

Posted 2023-03-29

【中文标题】如何在 R 中删除包含特定字符串的行？

【英文标题】：How can I delete a row containing a specific string in R?

【发布时间】：2019-04-25 22:15:42

【问题描述】：

我是使用 R 的新手。我正在使用一个数据集，并且缺失值已替换为“？”在我得到数据之前。我正在寻找一种方法来删除包含它的行。它不仅仅针对某一行，而是在所有行中。

我已经尝试过Delete rows containing specific strings in R，但它对我不起作用。到目前为止，我已经在下面包含了我的代码。

library(randomForest)
heart <- read.csv(url('http://archive.ics.uci.edu/ml/machine-learning-databases/echocardiogram/echocardiogram.data'))
names <- names(heart)
nrow(heart)
ncol(heart)
names(heart)

colnames(heart)[colnames(heart)=="X11"] <- "survival"
colnames(heart)[colnames(heart)=="X0"] <- "alive"
colnames(heart)[colnames(heart)=="X71"] <- "attackAge"
colnames(heart)[colnames(heart)=="X0.1"] <- "pericardialEffusion"
colnames(heart)[colnames(heart)=="X0.260"] <- "fractionalShortening"
colnames(heart)[colnames(heart)=="X9"] <- "epss"
colnames(heart)[colnames(heart)=="X4.600"] <- "lvdd"
colnames(heart)[colnames(heart)=="X14"] <- "wallMotionScore"
colnames(heart)[colnames(heart)=="X1"] <- "wallMotionIndex"
colnames(heart)[colnames(heart)=="X1.1"] <- "mult"
colnames(heart)[colnames(heart)=="name"] <- "patientName"
colnames(heart)[colnames(heart)=="X1.2"] <- "group"
colnames(heart)[colnames(heart)=="X0.2"] <- "aliveAfterYear"
names(heart)

【问题讨论】：

heart[rowSums(heart == "?") == 0, ]

看看?grepl

这些值是随机丢失还是故意丢失？也许 OP 应该考虑他或她是否应该保留或省略这些字符串。 na.omit 如下面的答案中所建议的那样，而一个好的选项并不总是适合 ML。

【参考方案1】：

library(randomForest)
heart <- read.csv(url('http://archive.ics.uci.edu/ml/machine-learning-databases/echocardiogram/echocardiogram.data'),na.strings = "?")
names <- names(heart)
nrow(heart)
ncol(heart)
names(heart)

colnames(heart)[colnames(heart)=="X11"] <- "survival"
colnames(heart)[colnames(heart)=="X0"] <- "alive"
colnames(heart)[colnames(heart)=="X71"] <- "attackAge"
colnames(heart)[colnames(heart)=="X0.1"] <- "pericardialEffusion"
colnames(heart)[colnames(heart)=="X0.260"] <- "fractionalShortening"
colnames(heart)[colnames(heart)=="X9"] <- "epss"
colnames(heart)[colnames(heart)=="X4.600"] <- "lvdd"
colnames(heart)[colnames(heart)=="X14"] <- "wallMotionScore"
colnames(heart)[colnames(heart)=="X1"] <- "wallMotionIndex"
colnames(heart)[colnames(heart)=="X1.1"] <- "mult"
colnames(heart)[colnames(heart)=="name"] <- "patientName"
colnames(heart)[colnames(heart)=="X1.2"] <- "group"
colnames(heart)[colnames(heart)=="X0.2"] <- "aliveAfterYear"
names(heart)


heart1 <- na.omit(heart)

在导入文件时，您可以将 na.string 指定为 ?稍后使用 na.omit 你可以删除所有的 ?或 NA 字符串

【参考方案2】：

我认为这可以做你想做的。

# Do not forget to set stringsAsFactors as false to the read.csv 
# as to make string comparison efficient
heart <- read.csv(url('http://archive.ics.uci.edu/ml/machine-learning-databases/echocardiogram/echocardiogram.data'),stringsAsFactors = F)

# Simpler way to assign column names to the dataframe
colnames(heart) <- c("survival", "alive", "attackAge", "pericardialEffusion", 
                     "fractionalShortening", "epss", "lvdd", "wallMotionScore", 
                     "wallMotionIndex", "mult", "patientName", 
                     "group", "aliveAfterYear")


# You can traverse a dataframe as a matrix using the row and column index 
# as coordinates 

for(r in 1:nrow(heart))
   for(c in 1:ncol(heart))
      # For this particular cell you do a comparison 
      # substituting the ? with NA which is the default missing value
      # in R 
      heart[r,c] <- ifelse(heart[r,c]=="?",NA,heart[r,c])
   


# omit the NA rows 
heart <- na.omit(heart)

【参考方案3】：

一些库支持读取 csv 文件并指定要作为缺失值读取的字符串。我最常使用readr 库。然后你就可以使用na.omit和类似的功能了。

library(readr)
library(dplyr)

heart  <- read_csv(
  'http://archive.ics.uci.edu/ml/machine-learning-databases/echocardiogram/echocardiogram.data',
  na=c("", "?")
)


colnames(heart) <- recode(
  colnames(heart),
  "X11" = "survival",
  "X0" = "alive",
  "X71" = "attackAge",
  "X0.1" = "pericardialEffusion",
  "X0.260" = "fractionalShortening",
  "X9" = "epss",
  "X4.600" = "lvdd",
  "X14" = "wallMotionScore",
  "X1" = "wallMotionIndex",
  "X1.1" = "mult",
  "name" = "patientName",
  "X1.2" = "group",
  "X0.2" = "aliveAfterYear"
  )

heart

heart <- na.omit(heart)

（您还可以使用 dplyr 包中的 recode 函数节省一些输入，但重命名列的解决方案效果很好。）