使用type.convert()和rapply()的通用方式:

convert_types <- function(x) {
    stopifnot(is.list(x))
    x[] <- rapply(x, utils::type.convert, classes = "character",
                  how = "replace", as.is = TRUE)
    return(x)
}
d <- data.frame(char = letters[1:5], 
                fake_char = as.character(1:5), 
                fac = factor(1:5), 
                char_fac = factor(letters[1:5]), 
                num = 1:5, stringsAsFactors = FALSE)
sapply(d, class)
#>        char   fake_char         fac    char_fac         num 
#> "character" "character"    "factor"    "factor"   "integer"
sapply(convert_types(d), class)
#>        char   fake_char         fac    char_fac         num 
#> "character"   "integer"    "factor"    "factor"   "integer"

与hablar::转换

要轻松地将多个列转换为不同的数据类型，可以使用hablar::convert。简单的语法:df %>% convert(num(a))将列a从df转换为数值。

详细的例子

让我们将mtcars的所有列转换为字符。

df <- mtcars %>% mutate_all(as.character) %>% as_tibble()

> df
# A tibble: 32 x 11
   mpg   cyl   disp  hp    drat  wt    qsec  vs    am    gear  carb 
   <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
 1 21    6     160   110   3.9   2.62  16.46 0     1     4     4    
 2 21    6     160   110   3.9   2.875 17.02 0     1     4     4    
 3 22.8  4     108   93    3.85  2.32  18.61 1     1     4     1    

与hablar::转换:

library(hablar)

# Convert columns to integer, numeric and factor
df %>% 
  convert(int(cyl, vs),
          num(disp:wt),
          fct(gear))

结果:

# A tibble: 32 x 11
   mpg     cyl  disp    hp  drat    wt qsec     vs am    gear  carb 
   <chr> <int> <dbl> <dbl> <dbl> <dbl> <chr> <int> <chr> <fct> <chr>
 1 21        6  160    110  3.9   2.62 16.46     0 1     4     4    
 2 21        6  160    110  3.9   2.88 17.02     0 1     4     4    
 3 22.8      4  108     93  3.85  2.32 18.61     1 1     4     1    
 4 21.4      6  258    110  3.08  3.22 19.44     1 0     3     1   

使用type.convert()和rapply()的通用方式:

convert_types <- function(x) {
    stopifnot(is.list(x))
    x[] <- rapply(x, utils::type.convert, classes = "character",
                  how = "replace", as.is = TRUE)
    return(x)
}
d <- data.frame(char = letters[1:5], 
                fake_char = as.character(1:5), 
                fac = factor(1:5), 
                char_fac = factor(letters[1:5]), 
                num = 1:5, stringsAsFactors = FALSE)
sapply(d, class)
#>        char   fake_char         fac    char_fac         num 
#> "character" "character"    "factor"    "factor"   "integer"
sapply(convert_types(d), class)
#>        char   fake_char         fac    char_fac         num 
#> "character"   "integer"    "factor"    "factor"   "integer"

要将数据帧列转换为数字，你只需要做:-

因数转换为数字:-

data_frame$column <- as.numeric(as.character(data_frame$column))

要将字符转换为数字，您必须通过应用将其转换为因数

BankFinal1 <- transform(BankLoan,   LoanApproval=as.factor(LoanApproval))
BankFinal1 <- transform(BankFinal1, LoanApp=as.factor(LoanApproval))

您必须用相同的数据创建两列，因为一列不能转换为数字。如果你做一次转换，它会给出如下错误

transform(BankData, LoanApp=as.numeric(LoanApproval))

警告信息: 在eval(替代(列表 (...)), `_ 数据”,parent.frame ()): 胁迫引入的NAs

所以，在做了两列相同的数据应用后

BankFinal1 <- transform(BankFinal1, LoanApp      = as.numeric(LoanApp), 
                                    LoanApproval = as.numeric(LoanApproval))

它将成功地将字符转换为数字

考虑到可能存在char列，这是基于@Abdou在获取列类型的excel表格自动回答:

makenumcols<-function(df){
  df<-as.data.frame(df)
  df[] <- lapply(df, as.character)
  cond <- apply(df, 2, function(x) {
    x <- x[!is.na(x)]
    all(suppressWarnings(!is.na(as.numeric(x))))
  })
  numeric_cols <- names(df)[cond]
  df[,numeric_cols] <- sapply(df[,numeric_cols], as.numeric)
  return(df)
}
df<-makenumcols(df)