Probably the best way is to handle the trailing whitespaces 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 w/o leading whitespace
trim.leading <- function (x) sub("^\\s+", "", x)
# returns string w/o trailing whitespace
trim.trailing <- function (x) sub("\\s+$", "", x)
# returns string w/o leading or trailing whitespace
trim <- function (x) gsub("^\\s+|\\s+$", "", x)
To use one of these functions on myDummy$country:
myDummy$country <- trim(myDummy$country)
To 'show' the whitespace you could use:
paste(myDummy$country)
which will show you the strings surrounded by quotation marks (") making whitespaces easier to spot.
If you want to clean strings afterwards you could use one of these functions:
# returns string w/o leading whitespace
trim.leading <- function (x) sub("^\\s+", "", x)
# returns string w/o trailing whitespace
trim.trailing <- function (x) sub("\\s+$", "", x)
# returns string w/o leading or trailing whitespace
trim <- function (x) gsub("^\\s+|\\s+$", "", x)
To use one of these functions on myDummy$country:
myDummy$country <- trim(myDummy$country)
To 'show' the whitespace you could use:
paste(myDummy$country)
which will show you the strings surrounded by quotation marks (") making whitespaces easier to spot.
rim {gdata} | R Documentation |
Remove leading and trailing spaces from character strings
Description
Remove leading and trailing spaces from character strings and other related objects.Usage
trim(s, recode.factor=TRUE, ...)
bob <- data.frame(lapply(bob, as.character), stringsAsFactors=FALSE)
bob[] <- lapply(bob, as.character)
bob[] <- lapply(bob, as.character)
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