I am trying to get anything existing between sample_id= and ; in a vector like this:
sample_id=10221108;gender=male
tissue_id=23;sample_id=321108;gender=male
treatment=no;tissue_id=98;sample_id=22
My desired output would be:
10221108
321108
22
How can I get this?
I've been trying several things like this, but I don't find the way to do it correctly:
clinical_data$sample_id<-c(sapply(myvector, function(x) sub("subject_id=.;", "\\1", x)))
You could use sub with a capture group to isolate that which you are trying to match:
out <- sub("^.*\\bsample_id=(\\d+).*$", "\\1", x)
out
[1] "10221108" "321108" "22"
Data:
x <- c("sample_id=10221108;gender=male",
"tissue_id=23;sample_id=321108;gender=male",
"treatment=no;tissue_id=98;sample_id=22")
Note that the actual output above is character, not numeric. But, you may easily convert using as.numeric if you need to do that.
Edit:
If you are unsure that the sample IDs would always be just digits, here is another version you may use to capture any content following sample_id:
out <- sub("^.*\\bsample_id=([^;]+).*$", "\\1", x)
out
You could try the str_extract method which utilizes the Stringr package.
If your data is separated by line, you can do:
str_extract("(?<=\\bsample_id=)([:digit:]+)") #this tells the extraction to target anything that is proceeded by a sample_id= and is a series of digits, the + captures all of the digits
This would extract just the numbers per line, if your data is all collected like that, it becomes a tad more difficult because you will have to tell the extraction to continue even if it has extracted something. The code would look something like this:
str_extract_all("((?<=sample_id=)\\d+)")
This code will extract all of the numbers you're looking for and the output will be a list. From there you can manipulate the list as you see fit.
Related
I just learnt R and was trying to clean data for analysis using R using string manipulation using the code given below for Amount_USD column of a table. I could not find why changes were not made. Please help.
Code:
csv_file2$Amount_USD <- ifelse(str_sub(csv_file$Amount_USD,1,10) == "\\\xc2\\\xa0",
str_sub(csv_file$Amount_USD,12,-1),csv_file2$Amount_USD)
Result:
\\xc2\\xa010,000,000
\\xc2\\xa016,200,000
\\xc2\\xa019,350,000
Expected Result:
10,000,000
16,200,000
19,350,000
You could use the following code, but maybe there is a more compact way:
vec <- c("\\xc2\\xa010,000,000", "\\xc2\\xa016,200,000", "\\xc2\\xa019,350,000")
gsub("(\\\\x[[:alpha:]]\\d\\\\x[[:alpha:]]0)([d,]*)", "\\2", vec)
[1] "10,000,000" "16,200,000" "19,350,000"
A compact way to extract the numbers is by using str_extract and negative lookahead:
library(stringr)
str_extract(vec, "(?!0)[\\d,]+$")
[1] "10,000,000" "16,200,000" "19,350,000"
How this works:
(?!0): this is negative lookahead to make sure that the next character is not 0
[\\d,]+$: a character class allowing only digits and commas to occur one or more times right up to the string end $
Alternatively:
str_sub(vec, start = 9)
There were a few minor issues with your code.
The main one being two unneeded backslashes in your matching statement. This also leads to a counting error in your first str_sub(), where you should be getting the first 8 characters not 10. Finally, you should be getting the substring from the next character after the text you want to match (i.e. position 9, not 12). The following should work:
csv_file2$Amount_USD <- ifelse(str_sub(csv_file$Amount_USD,1,8) == "\\xc2\\xa0", str_sub(csv_file$Amount_USD,9,-1),csv_file2$Amount_USD)
However, I would have done this with a more compact gsub than provided above. As long as the text at the start to remove is always going to be "\\xc2\\xa0", you can simply replace it with nothing. Note that for gsub you will need to escape all the backslashes, and hence you end up with:
csv_file2$Amount_USD <- gsub("\\\\xc2\\\\xa0", replacement = "", csv_file2$Amount_USD)
Personally, especially if you plan to do any sort of mathematics with this column, I would go the additional step and remove the commas, and then coerce the column to be numeric:
csv_file2$Amount_USD <- as.numeric(gsub("(\\\\xc2\\\\xa0)|,", replacement = "", csv_file2$Amount_USD))
This is what my text file looks like:
1241105.41129.97Y317052.03
2282165.61187.63N364051.40
2251175.87190.72Y366447.49
2243125.88150.81N276045.45
328192.89117.68Y295050.51
2211140.81165.77N346053.11
1291125.61160.61Y335048.3
3273127.73148.76Y320048.04
2191132.22156.94N336051.38
3221118.73161.03Y349349.5
2341189.01200.31Y360048.02
1253144.45180.96N305051.51
2251125.19152.75N305052.72
2192137.82172.25N240046.96
3351140.96174.85N394048.09
1233135.08173.36Y265049.82
1201112.59140.75N380051.25
2202128.19159.73N307048.29
2192132.82172.25Y240046.96
3351148.96174.85Y394048.09
1233132.08173.36N265049.82
1231114.59140.75Y380051.25
3442128.19159.73Y307048.29
2323179.18191.27N321041.12
All these values are continuous and each character indicates something. I am unable to figure out how to separate each value into columns and specify a heading for all these new columns which will be created.
I used this code, however it does not seem to work.
birthweight <- read.table("birthweighthw1.txt", sep="", col.names=c("ethnic","age","smoke","preweight","delweight","breastfed","brthwght","brthlngth”))
Any help would be appreciated.
Assuming that you have a clear definition for every column, you can use regular expressions to solve this in no time.
From your column names and example data, I guess that the regular expression that matches each field is:
ethnic: \d{1}
age: \d{1,2}
smoke: \d{1}
preweight: \d{3}\.\d{2}
delweight: \d{3}\.\d{2}
breastfed: Y|N
brthwght: \d{3}
brthlngth: \d{3}\.\d{1,2}
We can put all this together in a regular expression that captures each of these fields
reg.expression <- "(\\d{1})(\\d{1,2})(\\d{1})(\\d{3}\\.\\d{2})(\\d{3}\\.\\d{2})(Y|N)(\\d{3})(\\d{3}\\.\\d{1,2})"
Note: In R, we need to scape "\" that's why we write \d instead of \d.
That said, here comes the code to solve the problem.
First, you need to read your strings
lines <- readLines("birthweighthw1.txt")
Now, we define our regular expression and use the function str_match from the package stringr to get your data into character matrix.
require(stringr)
reg.expression <- "(\\d{1})(\\d{1,2})(\\d{1})(\\d{3}\\.\\d{2})(\\d{3}\\.\\d{2})(Y|N)(\\d{3})(\\d{3}\\.\\d{1,2})"
captured <- str_match(string= lines, pattern= reg.expression)
You can check that the first column in the matrix contains the text matched, and the following columns the data captured. So, we can get rid of the first column
captured <- captured[,-1]
and transform it into a data.frame with appropriate column names
result <- as.data.frame(captured,stringsAsFactors = FALSE)
names(result) <- c("ethnic","age","smoke","preweight","delweight","breastfed","brthwght","brthlngth")
Now, every column in result is of type character, you can transform each of them into other types. For example:
require(dplyr)
result <- result %>% mutate(ethnic=as.factor(ethnic),
age=as.integer(age),
smoke=as.factor(smoke),
preweight=as.numeric(preweight),
delweight=as.numeric(delweight),
breastfed=as.factor(breastfed),
brthwght=as.integer(brthwght),
brthlngth=as.numeric(brthlngth)
)
I am trying to subset a large data frame with my columns of interest. I do so using the grep function, this selects one column too many ("has_socio"), which I would like to remove.
The following code does exactly what I want, but I find it unpleasant to look at. I want to do it in one line. Aside from just calling the first subset inside the second subset, can it be optimized?
DF <- read.dta("./big.dta")
DF0 <- na.omit(subset(DF, select=c(other_named_vars, grep("has_",names(DF)))))
DF0 <- na.omit(subset(DF0, select=-c(has_socio)))
I know similar questions have been asked (e.g. Subsetting a dataframe in R by multiple conditions) but I do not find one that addresses this issue specifically. I recognize I could just write the grep RE more carefully, but I feel the above code more clearly expresses my intent.
Thanks.
Replace your grep with:
vec <- c("blah", "has_bacon", "has_ham", "has_socio")
grep("^has_(?!socio$)", vec, value=T, perl=T)
# [1] "has_bacon" "has_ham"
(?!...) is a negative lookahead operator, which looks ahead and makes sure that its contents do not follow the actual matching piece behind of it (has_ being the matching piece).
setdiff(grep("has_", vec, value = TRUE), "has_socio")
## [1] "has_bacon" "has_ham"
I have several datafiles, which I need to process in a particular order. The pattern of the names of the files is, e.g. "Ad_10170_75_79.txt".
Currently they are sorted according to the first numbers (which differ in length), see below:
f <- as.matrix (list.files())
f
[1] "Ad_10170_75_79.txt" "Ad_10345_76_79.txt" "Ad_1049_25_79.txt" "Ad_10531_77_79.txt"
But I need them to be sorted by the middle number, like this:
> f
[1] "Ad_1049_25_79.txt" "Ad_10170_75_79.txt" "Ad_10345_76_79.txt" "Ad_10531_77_79.txt"
As I just need the middle number of the filename, I thought the easiest way is, to get rid of the rest of the name and renaming all files. For this I tried using strsplit (plyr).
f2 <- strsplit (f,"_79.txt")
But I'm sure there is a way to sort the files directly, without renaming all files. I tried using sort and to describe the name with regex but without success. This has been a problem for many days, and I spent several hours searching and trying, to solve this presumably easy task. Any help is very much appreciated.
old example dataset:
f <- c("Ad_10170_75_79.txt", "Ad_10345_76_79.txt",
"Ad_1049_25_79.txt", "Ad_10531_77_79.txt")
Thank your for your answers. I think I have to modify my example, because the solution should work for all possible middle numbers, independent of their digits.
new example dataset:
f <- c("Ad_10170_75_79.txt", "Ad_10345_76_79.txt",
"Ad_1049_9_79.txt", "Ad_10531_77_79.txt")
Here's a regex approach.
f[order(as.numeric(gsub('Ad_\\d+_(\\d+)_\\d+\\.txt', '\\1', f)))]
# [1] "Ad_1049_9_79.txt" "Ad_10170_75_79.txt" "Ad_10345_76_79.txt" "Ad_10531_77_79.txt"
Try this:
f[order(as.numeric(unlist(lapply(strsplit(f, "_"), "[[", 3))))]
[1] "Ad_1049_25_79.txt" "Ad_10170_75_79.txt" "Ad_10345_76_79.txt" "Ad_10531_77_79.txt"
First we split by _, then select the third element of every list element, find the order and subset f based on that order.
I would create a small dataframe containing filenames and their respective extracted indices:
f<- c("Ad_10170_75_79.txt","Ad_10345_76_79.txt","Ad_1049_25_79.txt","Ad_10531_77_79.txt")
f2 <- strsplit (f,"_79.txt")
mydb <- as.data.frame(cbind(f,substr(f2,start=nchar(f2)-1,nchar(f2))))
names(mydb) <- c("filename","index")
library(plyr)
arrange(mydb,index)
Take the first column of this as your filename vector.
ADDENDUM:
If a numeric index is required, simply convert character to numeric:
mydb$index <- as.numeric(mydb$index)
I have a bunch of strings of mixed length, but all with a year embedded. I am trying to extract just the text part, that is everything until the number start and am having problem with lookeahead assertions assuming that is the proper way of such extractions.
Here is what I have (returns no match):
>grep("\\b.(?=\\d{4})","foo_1234_bar",perl=T,value=T)
In the example I am looking to extract just foo but there may be several, and of mixed lengths, separated by _ before the year portion.
Look-aheads may be overkill here. Use the underscore and the 4 digits as the structure, combined with a non-greedy quantifier to prevent the 'dot' from gobbling up everything:
/(.+?)_\d{4}/
-first matching group ($1) holds 'foo'
This will grab everything up until the first digit
x <- c("asdfas_1987asdf", "asd_das_12")
regmatches(x, regexpr("^[^[:digit:]]*", x))
#[1] "asdfas_" "asd_das_"
Another approach (often I find that strsplit is faster than regex searching but not always (though this does use a slight bit of regexing):
x <- c("asdfas_1987asdf", "asd_das_12") #shamelessly stealing Dason's example
sapply(strsplit(x, "[0-9]+"), "[[", 1)