Probably the best way is to handle the trailing white spaces when you read your data file. If you use read.csv or read.table you can set the parameterstrip.white=TRUE.

If you want to clean strings afterwards you could use one of these functions:

# Returns string without leading white space
trim.leading <- function (x)  sub("^\s+", "", x)

# Returns string without trailing white space
trim.trailing <- function (x) sub("\s+$", "", x)

# Returns string without leading or trailing white space
trim <- function (x) gsub("^\s+|\s+$", "", x)

To use one of these functions on myDummy$country:

 myDummy$country <- trim(myDummy$country)

To show the white space you could use:

 paste(myDummy$country)

which will show you the strings surrounded by quotation marks (") making white spaces easier to spot.

As of R 3.2.0 a new function was introduced for removing leading/trailing white spaces:

trimws()

See: Remove Leading/Trailing Whitespace

To manipulate the white space, use str_trim() in the stringr package. The package has manual dated Feb 15, 2013 and is in CRAN. The function can also handle string vectors.

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

(Credit goes to commenter: R. Cotton)

A simple function to remove leading and trailing whitespace:

trim <- function( x ) {
  gsub("(^[[:space:]]+|[[:space:]]+$)", "", x)
}

Usage:

> text = "   foo bar  baz 3 "
> trim(text)
[1] "foo bar  baz 3"

Ad 1) To see white spaces you could directly call print.data.frame with modified arguments:

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"

See also ?print.data.frame for other options.

Use grep or grepl to find observations with white spaces and sub to get rid of them.

names<-c("Ganga Din	", "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"

Removing leading and trailing blanks might be achieved through the trim() function from the gdata package as well:

require(gdata)
example(trim)

Usage example:

> trim("   Remove leading and trailing blanks    ")
[1] "Remove leading and trailing blanks"

_{I d prefer to add the answer as comment to user56 s, but I am yet unable so writing as an independent answer.}

Another option is to use the stri_trim function from the stringi package which defaults to removing leading and trailing whitespace:

> x <- c("  leading space","trailing space   ")
> stri_trim(x)
[1] "leading space"  "trailing space"

For only removing leading whitespace, use stri_trim_left. For only removing trailing whitespace, use stri_trim_right. When you want to remove other leading or trailing characters, you have to specify that with pattern =.

See also ?stri_trim for more info.

Another related problem occurs if you have multiple spaces in between inputs:

> a <- "  a string         with lots   of starting, inter   mediate and trailing   whitespace     "

You can then easily split this string into "real" tokens using a regular expression to the split argument:

> strsplit(a, split=" +")
[[1]]
 [1] ""           "a"          "string"     "with"       "lots"
 [6] "of"         "starting,"  "inter"      "mediate"    "and"
[11] "trailing"   "whitespace"

Note that if there is a match at the beginning of a (non-empty) string, the first element of the output is ‘""’, but if there is a match at the end of the string, the output is the same as with the match removed.

I created a trim.strings () function to trim leading and/or trailing whitespace as:

# Arguments:    x - character vector
#            side - side(s) on which to remove whitespace 
#                   default : "both"
#                   possible values: c("both", "leading", "trailing")

trim.strings <- function(x, side = "both") { 
    if (is.na(match(side, c("both", "leading", "trailing")))) { 
      side <- "both" 
      } 
    if (side == "leading") { 
      sub("^\s+", "", x)
      } else {
        if (side == "trailing") {
          sub("\s+$", "", x)
    } else gsub("^\s+|\s+$", "", x)
    } 
} 

For illustration,

a <- c("   ABC123 456    ", " ABC123DEF          ")

# returns string without leading and trailing whitespace
trim.strings(a)
# [1] "ABC123 456" "ABC123DEF" 

# returns string without leading whitespace
trim.strings(a, side = "leading")
# [1] "ABC123 456    "      "ABC123DEF          "

# returns string without trailing whitespace
trim.strings(a, side = "trailing")
# [1] "   ABC123 456" " ABC123DEF"   

Use dplyr/tidyverse mutate_all with str_trim to trim the entire data frame:

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"

^{Created on 2021-05-07 by the reprex package (v0.3.0)}

The best method is trimws().

The following code will apply this function to the entire dataframe.

mydataframe<- data.frame(lapply(mydataframe, trimws),stringsAsFactors = FALSE)

I tried trim(). It works well with white spaces as well as the .

x =  
              Harden, J.
               

trim(x)

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

After this, you ll need to force R not to recognize "Austria " as a level. Let s pretend you also have "USA" and "Spain" as levels:

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

It is a little less intimidating than the highest voted response, but it should still work.

Benchmarking of the main approaches in this thread. This is not capturing all weird cases, but so far we are still lacking the example where str_trim removes whitespace and trimws doesn t (see Richard Telford s comment to this answer). Doesn t seem to matter - the gsub option seems to be fastest :)

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