解析"NA"字符串中的引号

要添加替代方案,您还可以使用replace代替典型blah[index] <- NA方法.replace看起来像:

df <- replace(df, df == "NA", NA)

另一个需要考虑的选择是type.convert.这是R在读取数据时使用的函数,用于自动转换列类型.因此,结果与您当前的方法不同,例如,第二列转换为数字.

df[] <- lapply(df, function(x) type.convert(as.character(x), na.strings = "NA"))
df

这是性能比较.样本数据来自@ roland的回答.

以下是要测试的功能:

funop <- function() {
  df[df == "NA"] <- NA
  df
}

funr <- function() {
  ind <- which(vapply(df, function(x) class(x) %in% c("character", "factor"), FUN.VALUE = TRUE))
  as.data.table(df)[, names(df)[ind] := lapply(.SD, function(x) {
    is.na(x) <- x == "NA"
    x
  }), .SDcols = ind][]
}

funam1 <- function() replace(df, df == "NA", NA)

funam2 <- function() {
  df[] <- lapply(df, function(x) type.convert(as.character(x), na.strings = "NA"))
  df
}

这是基准测试:

library(microbenchmark)
microbenchmark(funop(), funr(), funam1(), funam2(), times = 10)
# Unit: seconds
#      expr      min       lq     mean   median       uq      max neval
#   funop() 3.629832 3.750853 3.909333 3.855636 4.098086 4.248287    10
#    funr() 3.074825 3.212499 3.320430 3.279268 3.332304 3.685837    10
#  funam1() 3.714561 3.899456 4.238785 4.065496 4.280626 5.512706    10
#  funam2() 1.391315 1.455366 1.623267 1.566486 1.606694 2.253258    10

replace与@ roland的方法相同,这与@ jgozal的方法相同.但是,该type.convert方法会导致不同的列类型.

all.equal(funop(), setDF(funr()))
all.equal(funop(), funam())

str(funop())
# 'data.frame': 10000000 obs. of  3 variables:
#  $ vect1: Factor w/ 3 levels "BANANA","HELLO",..: 2 2 NA 2 1 1 1 NA 1 1 ...
#  $ vect2: Factor w/ 3 levels "1","5","NA": NA 2 1 NA 1 NA NA 1 NA 2 ...
#  $ vect3: Factor w/ 1 level "NA": NA NA NA NA NA NA NA NA NA NA ...

str(funam2())
# 'data.frame': 10000000 obs. of  3 variables:
#  $ vect1: Factor w/ 2 levels "BANANA","HELLO": 2 2 NA 2 1 1 1 NA 1 1 ...
#  $ vect2: int  NA 5 1 NA 1 NA NA 1 NA 5 ...
#  $ vect3: logi  NA NA NA NA NA NA ...