我有一些麻烦的前导和尾随空白在一个数据。框架。

例如,我根据特定条件查看data.frame中的特定行:

> myDummy[myDummy$country == c("Austria"),c(1,2,3:7,19)] 



[1] codeHelper     country        dummyLI    dummyLMI       dummyUMI       

[6] dummyHInonOECD dummyHIOECD    dummyOECD      

<0 rows> (or 0-length row.names)

我想知道为什么我没有得到预期的输出,因为奥地利显然存在于我的数据框架中。在查看了我的代码历史并试图找出错误后,我尝试了:

> myDummy[myDummy$country == c("Austria "),c(1,2,3:7,19)]
   codeHelper  country dummyLI dummyLMI dummyUMI dummyHInonOECD dummyHIOECD
18        AUT Austria        0        0        0              0           1
   dummyOECD
18         1

我所更改的命令只是在奥地利之后增加了一个空白。

显然还会出现更多烦人的问题。例如,当我喜欢根据国家列合并两帧时。一个data.frame使用“Austria”,而另一个frame使用“Austria”。匹配不起作用。

有没有一种很好的方法来“显示”屏幕上的空白,让我意识到这个问题? 我能移除R开头和结尾的空白吗?

到目前为止,我曾经写过一个简单的Perl脚本,它消除了白色的速度,但如果我能以某种方式在R中做到这一点就好了。


当前回答

myDummy[myDummy$country == "Austria "] <- "Austria"

在这之后,你需要强制R不承认“奥地利”是一个关卡。让我们假设你也有“USA”和“Spain”作为关卡:

myDummy$country = factor(myDummy$country, levels=c("Austria", "USA", "Spain"))

这比得票最高的回答要少一些威慑力,但它仍然有效。

其他回答

本线程中主要方法的基准测试。这并没有捕捉到所有奇怪的情况,但到目前为止,我们仍然缺少str_trim删除空格而trimws不删除空格的示例(参见Richard Telford对这个答案的评论)。似乎并不重要- gsub选项似乎是最快的:)

x <- c(" lead", "trail ", " both ", " both and middle ", " _special")
## gsub function from https://stackoverflow.com/a/2261149/7941188 
## this is NOT the function from user Bernhard Kausler, which uses 
## a much less concise regex 
gsub_trim <- function (x) gsub("^\\s+|\\s+$", "", x)

res <- microbenchmark::microbenchmark(
  gsub = gsub_trim(x),
  ## https://stackoverflow.com/a/30210713/7941188
  trimws = trimws(x),
  ## https://stackoverflow.com/a/15007398/7941188
  str_trim = stringr::str_trim(x),
  times = 10^5
)
res
#> Unit: microseconds
#>      expr    min     lq      mean median       uq       max neval cld
#>      gsub 20.201 22.788  31.43943 24.654  28.4115  5303.741 1e+05 a  
#>    trimws 38.204 41.980  61.92218 44.420  51.1810 40363.860 1e+05  b 
#>  str_trim 88.672 92.347 116.59186 94.542 105.2800 13618.673 1e+05   c
ggplot2::autoplot(res)

sessionInfo()
#> R version 4.0.3 (2020-10-10)
#> Platform: x86_64-apple-darwin17.0 (64-bit)
#> Running under: macOS Big Sur 10.16
#> 
#> locale:
#> [1] en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8
#> 
#> attached base packages:
#> [1] stats     graphics  grDevices utils     datasets  methods   base     
#> 
#> loaded via a namespace (and not attached):
#>  stringr_1.4.0  

使用dplyr/tidyverse mutate_all和str_trim来修剪整个数据帧:

myDummy %>%
  mutate_all(str_trim)
library(tidyverse)
set.seed(335)
df <- mtcars %>%
        rownames_to_column("car") %>%
        mutate(car = ifelse(runif(nrow(mtcars)) > 0.4, car, paste0(car, " "))) %>%
        select(car, mpg)

print(head(df), quote = T)
#>                    car    mpg
#> 1         "Mazda RX4 " "21.0"
#> 2      "Mazda RX4 Wag" "21.0"
#> 3        "Datsun 710 " "22.8"
#> 4    "Hornet 4 Drive " "21.4"
#> 5 "Hornet Sportabout " "18.7"
#> 6           "Valiant " "18.1"

df_trim <- df %>%
  mutate_all(str_trim)

print(head(df_trim), quote = T)  
#>                   car    mpg
#> 1         "Mazda RX4"   "21"
#> 2     "Mazda RX4 Wag"   "21"
#> 3        "Datsun 710" "22.8"
#> 4    "Hornet 4 Drive" "21.4"
#> 5 "Hornet Sportabout" "18.7"
#> 6           "Valiant" "18.1"

由reprex包于2021-05-07创建(v0.3.0)

1)要查看空白,可以直接调用print.data.frame,并修改参数:

print(head(iris), quote=TRUE)
#   Sepal.Length Sepal.Width Petal.Length Petal.Width  Species
# 1        "5.1"       "3.5"        "1.4"       "0.2" "setosa"
# 2        "4.9"       "3.0"        "1.4"       "0.2" "setosa"
# 3        "4.7"       "3.2"        "1.3"       "0.2" "setosa"
# 4        "4.6"       "3.1"        "1.5"       "0.2" "setosa"
# 5        "5.0"       "3.6"        "1.4"       "0.2" "setosa"
# 6        "5.4"       "3.9"        "1.7"       "0.4" "setosa"

其他选项请参见?print.data.frame。

使用grep或grepl查找带有空格的观测值,并使用sub删除它们。

names<-c("Ganga Din\t", "Shyam Lal", "Bulbul ")
grep("[[:space:]]+$", names)
[1] 1 3
grepl("[[:space:]]+$", names)
[1]  TRUE FALSE  TRUE
sub("[[:space:]]+$", "", names)
[1] "Ganga Din" "Shyam Lal" "Bulbul"

要操作空格,请使用stringr包中的str_trim()。 包装上有2013年2月15日的手册,并在CRAN中。 该函数还可以处理字符串向量。

install.packages("stringr", dependencies=TRUE)
require(stringr)
example(str_trim)
d4$clean2<-str_trim(d4$V2)

(图片来源:R. Cotton)