I have a data set that contains strings and special characters like the one below can be found in the data set.
Special character
How do I remove special characters like the above from my data set?
Use regular expressions to remove unwanted characters, for example:
dataset$textcolumn <- gsub("[^\\w\\s]", "", dataset$textcolumn, perl=TRUE)
to remove everything except word characters and spaces. To do more complex replacements look into the help topic ?regexp.
Also look into the encoding (Encoding and iconv are helpful here.), maybe the text is correct but the wrong encoding is assumed.
Related
I'm working with the following code:
Y_Columns <- c("Y.1.1")
paste('{"ImportId":"', Y_Columns, '"}', sep = "")
The paste function produces the following output:
"{\"ImportId\":\"Y.1.1\"}"
How do I get the paste function to omit the \? Such that, the output is:
"{"ImportId":"Y.1.1"}"
Thank you for your help.
Note: I did do a search on SO to see if there were any Q's that asked "what is an escape character in R". But I didn't review all the 160 answers, only the first 20.
This is one way of demonstrating what I wrote in my comment:
out <- paste('{"ImportId":"', Y_Columns, '"}', sep = "")
out
#[1] "{\"ImportId\":\"Y.1.1\"}"
?print
print(out,quote=FALSE)
#[1] {"ImportId":"Y.1.1"}
Both R and regex patterns use escape characters to allow special characters to be displayed in print output or input. (And sometimes regex patterns need to have doubled escapes.) R has a few characters that need to be "escaped" in certain situation. You illustrated one such situation: including double-quote character inside a result that will be printed with surrounding double-quotes. If you were intending to include any single quotes inside a character value that was delimited by single quotes at the time of creation, they would have needed to be escaped as well.
out2 <- '\'quoted\''
nchar(out2)
#[1] 8 ... note that neither the surround single-quotes nor the backslashes get counted
> out2
[1] "'quoted'" ... and the default output quote-char is a double-quote.
Here's a good Q&A to review:How to replace '+' using gsub() function in R
It has two answers, both useful: one shows how to double escape a special character and the other shows how to use teh fixed argument to get around that requirement.
And another potentially useful Q&A on the topic of handling Windows paths:
File path issues in R using Windows ("Hex digits in character string" error)
And some further useful reading suggestions: Look at the series of help pages that start with capital letters. (Since I can never remember which one has which nugget of essential information, I tried ?Syntax first and it has a "See Also" list of essential reading: Arithmetic, Comparison, Control, Extract, Logic, NumericConstants, Paren, Quotes, Reserved. and I then realized what I wanted to refer you to was most likely ?Quotes where all the R-specific escape sequence letters should be listed.
I have a json string that's is a nested dataframe and is full of characters that need to be escaped like \n, \r and \. I have not been able to convert it with jsonlite.
Here's a dput of the first element of the list.
fromJSON(json_data) gives the following error:
Replacing the character "{" with blank character is not working.
Any help would be greatly appreciated.
This solution is meant to be a stop-gap for one known flaw in the json validation: two (or more) dictionaries are not separated by a comma. I discourage the use of regular expressions to fix this, but a fixed string-replacement can suffice:
json_date <- gsub("} {", "},{", json_data, fixed = TRUE)
When doing some textual data cleaning in R, I can found some special characters. In order to get rid of them, I have to know their unicodes, for example € is \u20AC. I would like to know if it is possible "see" the unicodes with a function that take into account the string within the special character as an input?
Refering to Cath comment, iconv can do the job :
iconv("é", toRaw = TRUE)
Then, you may want to unlist and paste with \u00.
special_char <- "%"
Unicode::as.u_char(utf8ToInt(special_char))
I'm almost certain this has been asked before but due to a certain social media app I drowning in unrelated search results.
So the data set that I'm importing contains actual "#", as in Apartment #404, and I'd like to if possible preserve the character but R thinks it's an end of line or something. At first it would bomb out on the first occurrence, then I set fill=TRUE and now it just ignores the rest of the line after that.
How does one instruct R to treat #'s as regular characters?
If you are not using "#" as a comment symbol in your data, you can use
read.table(..., comment.char="")
That should treat "#" like any other character.
I've been using gsub("toreplace","replacement", myvector) to clean out data in R. While this works for commas and the like, removing "$" has no effect. So if I do gsub("$","",myvector) all the dollar signs remain in place.
I think this is because $ is a special character in R. I tried escaping it "\$" but that yields the same result (no effect). And I couldn't find a resource on escaping special characters in R.
Obviously I should do this in preprocessing. But I was wondering if anyone out there knew how to either a) escape special characters in R b) get rid of pesky $ in R directly. For science.
You have to escape it twice, first for R, second for the regex.
gsub('\\$', '', c("a$a", "bb$"))
[1] "aa" "bb"
See ?Quotes for details on quoting and escaping.
Use fixed = TRUE:
gsub('$', '', c("a$a", "bb$"), fixed = TRUE)
Then you don't need to worry about any special characters. In stringr, this is implemented a little differently:
library(stringr)
str_replace_all(c("$100","ta$ty"), fixed("$"), "")
Thanks to DiggyF and James for the examples!
Escaping characters can be a pain some times, but just putting it in square brackets (make it a character class) helps with this:
> gsub("[$]","",c("$100","ta$ty"))
[1] "100" "taty"
if you have $ followed by number in set of data columns (e.g. $400,000) there is an easier way that worked like charm for me.
data%>%
mutate_at(5:6, parse_number)
where 5:6 are the data column numbers.