I want to clean up strings so they can be parsed as unique legal symbols. I intend to clean up a lot of strings, so there is an undesirable risk of duplicated symbols in the output. It would suffice to take every illegal character and replace it with its base 32 encoding. Desired behavior:
sanitize("_bad_symbol$not*a&list%$('")
## [1] "L4bad_symbolEQnotFIaEYlistEUSCQJY"
I think all I need is a complete list of possible characters to grep for. I know about letters and LETTERS, but what about everything else?
Does a better solution already exist? Because I would love that.
EDIT: just found about make.names() from this post. I could go with that in a pinch, but I would rather not.
With make.names() and make.unique() together, the problem is solved.
make.unique(make.names(c("asdflkj###$", "asdflkj####")))
## [1] "asdflkj...." "asdflkj.....1"
Related
I have a column within a data frame with a series of identifiers in, a letter and 8 numbers, i.e. B15006788.
Is there a way to remove all instances of B15.... to make them empty cells (there’s thousands of variations of numbers within each category) but keep B16.... etc?
I know if there was just one thing I wanted to remove, like the B15, I could do;
sub(“B15”, ””, df$col)
But I’m not sure on the how to remove a set number of characters/numbers (or even all subsequent characters after B15).
Thanks in advance :)
Welcome to SO! This is a case of regex. You can use base R as I show here or look into the stringR package for handy tools that are easier to understand. You can also look for regex rules to help define what you want to look for. For what you ask you can use the following code example to help:
testStrings <- c("KEEPB15", "KEEPB15A", "KEEPB15ABCDE")
gsub("B15.{2}", "", testStrings)
gsub is the base R function to replace a pattern with something else in one or a series of inputs. To test our regex I created the testStrings vector for different examples.
Breaking down the regex code, "B15" is the pattern you're specifically looking for. The "." means any character and the "{2}" is saying what range of any character we want to grab after "B15". You can change it as you need. If you want to remove everything after "B15". replace the pattern with "B15.". the "" means everything till the end.
edit: If you want to specify that "B15" must be at the start of the string, you can add "^" to the start of the pattern as so: "^B15.{2}"
https://www.rstudio.com/wp-content/uploads/2016/09/RegExCheatsheet.pdf has a info on different regex's you can make to be more particular.
I have been mucking around with regex strings and strsplit but can't figure out how to solve my problem.
I have a collection of html documents that will always contain the phrase "people own these". I want to extract the number immediately preceding this phrase. i.e. '732,234 people own these' - I'm hoping to capture the number 732,234 (including the comma, though I don't care if it's removed).
The number and phrase are always surrounded by a . I tried using Xpath but that seemed even harder than a regex expression. Any help or advice is greatly appreciated!
example string: >742,811 people own these<
-> 742,811
Could you please try following.
val <- "742,811 people own these"
gsub(' [a-zA-Z]+',"",val)
Output will be as follows.
[1] "742,811"
Explanation: using gsub(global substitution) function of R here. Putting condition here where it should replace all occurrences of space with small or capital alphabets with NULL for variable val.
Try using str_extract_all from the stringr library:
str_extract_all(data, "\\d{1,3}(?:,\\d{3})*(?:\\.\\d+)?(?= people own these)")
(strap in!)
Hi, I'm running into issues involving Unicode encoding in R.
Basically, I'm importing data sets that contain Unicode (UTF-8) characters, and then running grep() searches to match values. For example, say I have:
bigData <- c("foo","αβγ","bar","αβγγ (abgg)", ...)
smallData <- c("αβγ","foo", ...)
What I'm trying to do is take the entries in smallData and match them to entries in bigData. (The actual sets are matrixes with columns of values, so what I'm trying to do is find the indexes of the matches, so I can tell what row to add the values to.) I've been using
matches <- grepl(smallData[i], bigData, fixed=T)
which usually results in a vector of matches. For i=2, it would return 1, since "foo" is element 1 of bigData. This is peachy and all is well. But RStudio seems to not be dealing with unicode characters properly. When I import the sets and view them, they use the character IDs.
dataset <- read_csv("[file].csv", col_names = FALSE, locale = locale())
Using View(dataset) shows "aß<U+03B3>" instead of "αβγ." The same goes for
dataset[1]
A tibble: 1x1 <chr>
[1] aß<U+03B3>
print(dataset[1])
A tibble: 1x1 <chr>
[1] aß<U+03B3>
However, and this is why I'm stuck rather than just adjusting the encoding:
paste(dataset[1])
[1] "αβγ"
Encoding(toString(dataset[1]))
[1] "UTF-8"
So it appears that R is recognizing in certain contexts that it should display Unicode characters, while in others it just sticks to--ASCII? I'm not entirely sure, but certainly a more limited set.
In any case, regardless of how it displays, what I want to do is be able to get
grep("αβγ", bigData)
[1] 2 4
However, none of the following work:
grep("αβ", bigData) #(Searching the two letters that do appear to convert)
grep("<U+03B3>",bigData,fixed=T) #(Searching the code ID itself)
grep("αβ", toString(bigData)) #(converts the whole thing to one string)
grep("\\β", bigData) #(only mentioning because it matches, bizarrely, to ß)
The only solution I've found is:
grep("\u03B3", bigData)
[1] 2 4
Which is not ideal for a couple reasons, most jarringly that it doesn't look like it's possible to just take every <U+####> and replace it with \u####, since not every Unicode character is converted to the <U+####> format, but none of them can be searched. (i.e., α and ß didn't turn into their unicode keys, but they're also not searchable by themselves. So I'd have to turn them into their keys, then alter their keys to a form that grep() can use, then search.)
That means I can't just regex the keys into a searchable format--and even if I could, I have a lot of entries including characters that'd need to be escaped (e.g., () or ), so having to remove the fixed=T term would be its own headache involving nested escapes.
Anyway...I realize that a significant part of the problem is that my set apparently involves every sort of character under the sun, and it seems I have thoroughly entrapped myself in a net of regular expressions.
Is there any way of forcing a search with (arbitrary) unicode characters? Or do I have to find a way of using regular expressions to escape every ( and α in my data set? (coordinate to that second question: is there a method to convert a unicode character to its key? I can't seem to find anything that does that specific function.)
I am using the following code for finding number of occurrences of a word memory in a file and I am getting the wrong result. Can you please help me to know what I am missing?
NOTE1: The question is looking for exact occurrence of word "memory"!
NOTE2: What I have realized they are exactly looking for "memory" and even something like "memory," is not accepted! That was the part which has brought up the confusion I guess. I tried it for word "action" and the correct answer is 7! You can try as well.
#names=scan("hamlet.txt", what=character())
names <- scan('http://pastebin.com/raw.php?i=kC9aRvfB', what=character())
Read 28230 items
> length(grep("memory",names))
[1] 9
Here's the file
The problem is really Shakespeare's use of punctuation. There are a lot of apostrophes (') in the text. When the R function scan encounters an apostrophe it assumes it is the start of a quoted string and reads all characters up until the next apostrophe into a single entry of your names array. One of these long entries happens to include two instances of the word "memory" and so reduces the total number of matches by one.
You can fix the problem by telling scan to regard all quotation marks as normal characters and not treat them specially:
names <- scan('http://pastebin.com/raw.php?i=kC9aRvfB', what=character(), quote=NULL )
Be careful when using the R implementation of grep. It does not behave in exactly the same way as the usual GNU/Linux program. In particular, the way you have used it here WILL find the number of matching words and not just the total number of matching lines as some people have suggested.
As pointed by #andrew, my previous answer would give wrong results if a word repeats on the same line. Based on other answers/comments, this one seems ok:
names = scan('http://pastebin.com/raw.php?i=kC9aRvfB', what=character(), quote=NULL )
idxs = grep("memory", names, ignore.case = TRUE)
length(idxs)
# [1] 10
The text to be checked is in Greek, but I would like to know if it can be done for English words too. My initial idea is described here, and I have already found a way to do it using VBA. But I wonder if there's a way to do it using R. If there isn't a way in R, do you think of something better than Excel-vba?
Alternatively, OpenOffice ships with a dictionary that entries stored in a text file. You can read that and remove the word definitions to create your word list.
This was tested on v3.0; the file location may have shifted, and the filename will change depending on which dictionary you want.
library(stringr)
dict <- readLines("C:/Program Files/OpenOffice.org 3/share/uno_packages/cache/uno_packages/174.tmp_/dict-en.oxt/th_en_US_v2.dat")
is_word <- str_detect(dict, "^[^(]")
words <- str_split_fixed(dict[is_word], "\\|", 2)
words <- words[,1]
This list contains some multi-word phrases. You may prefer to split on the first space, and take unique values. You probably also want to write words to file, to save repeating yourself.
Once this is done, checking a word is as easy as
c("persnickety", "sqwrzib") %in% words # TRUE FALSE
There exists an open source GNU spell checker called Aspell with suppot for various languages. This is a command line program which I basically use for scanning bunches of text files at once (then the output is just given to the console).
But there also exists a C API and perhaps more interesting for you a Pipe mode which accepts streams of texts and outputs to the standard output.
Hope this helps.