R: split string & assign variable based on split

Question

I have a single field of semantic tags & semantic tag types. Each tag type/tag is comma-separated, while each tag type & tag are colon separated (see below).

ID | Semantic Tags

1  |   Person:mitch mcconnell, Person:ashley judd, Position:senator

2  |   Person:mitch mcconnell, Position:senator, ProvinceOrState:kentucky, topicname:politics 

3  |   Person:mitch mcconnell, Person:ashley judd, Organization:senate, Organization:republican 

4  |   Person:ashley judd, topicname:politics

5  |   URL:www.huffingtonpost.com, Company:usa today, Person:chuck todd, Company:msnbc

I want to split each tag type (term before colon) & tag (term after colon) into two separate fields: "Tag Type" & "Tag". The resulting file should look something like this:

ID | Tag Type  |  Tag

1  |  Person   |  mitch McConnell

1  |  Person   |  ashley judd  

1  |  Position |  senator

2  |  Person   |  mitch McConnell

2  |  Position |  senator

2  |  State    |  kentucky

Here is the code I have so far...

tag<-strsplit(as.character(emtable$Symantic.Tags),","))
tagtype<-strsplit(as.character(tag),":")

But after that, I'm lost! I believe I need to use lapply or sapply for this, but am not sure where that plays in...

My apologies if this has been answered in other forms on the site -- I am new to R & this is still a bit complex for me.

Thanks in advance for anyone's help.

Tyler Rinker · Accepted Answer

This is another (slightly different) approach:

## dat <- readLines(n=5)
## Person:mitch mcconnell, Person:ashley judd, Position:senator
## Person:mitch mcconnell, Position:senator, ProvinceOrState:kentucky, topicname:politics
## Person:mitch mcconnell, Person:ashley judd, Organization:senate, Organization:republican
## Person:ashley judd, topicname:politics
## URL:www.huffingtonpost.com, URL:http://www.regular-expressions.info

dat3 <- lapply(strsplit(dat, ","), function(x) gsub("^\s+|\s+$", "", x))
#dat3 <- lapply(dat2, function(x) x[grepl("Person|Position", x)]) 
dat3 <- lapply(dat3, strsplit, ":(?!/)", perl=TRUE) #break on : not folled by /
dat3 <- data.frame(ID=rep(seq_along(dat3), sapply(dat3, length)),
    do.call(rbind, lapply(dat3, function(x) do.call(rbind, x)))
)

colnames(dat3)[-1] <- c("Tag Type", "Tag")

##    ID        Tag Type                    Tag
## 1   1          Person        mitch mcconnell
## 2   1          Person            ashley judd
## 3   1        Position                senator
## 4   2          Person        mitch mcconnell
## 5   2        Position                senator
## 6   2 ProvinceOrState               kentucky
## 7   2       topicname               politics
## 8   3          Person        mitch mcconnell
## 9   3          Person            ashley judd
## 10  3    Organization                 senate
## 11  3    Organization             republican
## 12  4          Person            ashley judd
## 13  4       topicname               politics
## 14  5             URL www.huffingtonpost.com
## 15  5         Company              usa today
## 16  5          Person             chuck todd
## 17  5         Company                  msnbc

Thorough explanation:

## dat <- readLines(n=5)
## Person:mitch mcconnell, Person:ashley judd, Position:senator
## Person:mitch mcconnell, Position:senator, ProvinceOrState:kentucky, topicname:politics
## Person:mitch mcconnell, Person:ashley judd, Organization:senate, Organization:republican
## Person:ashley judd, topicname:politics
## URL:www.huffingtonpost.com, URL:http://www.regular-expressions.info

dat3 <- lapply(strsplit(dat, ","), function(x) gsub("^\s+|\s+$", "", x))
#dat3 <- lapply(dat2, function(x) x[grepl("Person|Position", x)]) 
dat3 <- lapply(dat3, strsplit, ":(?!/)", perl=TRUE) #break on : not folled by /

# Let the explanation begin...

# Here I have a short list of the variables from the rows
# of the original dataframe; in this case the row numbers:

seq_along(dat3)      #row variables

# then I use sapply and length to figure out hoe long the
# split variables in each row (now a list) are

sapply(dat3, length) #n times

# this tells me how many times to repeat the short list of 
# variables.  This is because I stretch the dat3 list to a vector
# Here I rep the row variables n times

rep(seq_along(dat3), sapply(dat3, length))

# better assign that for later:

ID <- rep(seq_along(dat3), sapply(dat3, length))

#============================================
# Now to explain the next chunk...
# I take dat3

dat3

# Each element in the list 1-5 is made of a new list of 
# Vectors of length 2 of Tag_Types and Tags.
# For instance here's element 5 a list of two  lists 
# with character vectors of length 2 

## [[5]]
## [[5]][[1]]
## [1] "URL"  "www.huffingtonpost.com"
## 
## [[5]][[2]]
## [1] "URL"  "http://www.regular-expressions.info"

# Use str to look at this structure:

dat3[[5]]
str(dat3[[5]])

## List of 2
##  $ : chr [1:2] "URL" "www.huffingtonpost.com"
##  $ : chr [1:2] "URL" "http://www.regular-expressions.info"

# I use lapply (list apply) to apply an anynomous function:
# function(x) do.call(rbind, x) 
#
# TO each of the 5 elements.  This basically glues the list 
# of vectors together to make a matrix.  Observe just on elenet 5:

do.call(rbind, dat3[[5]])

##      [,1]  [,2]                                 
## [1,] "URL" "www.huffingtonpost.com"             
## [2,] "URL" "http://www.regular-expressions.info"

# We use lapply to do that to all elements:

lapply(dat3, function(x) do.call(rbind, x))

# We then use the do.call(rbind on this list and we have a 
# matrix

do.call(rbind, lapply(dat3, function(x) do.call(rbind, x)))

# Let's assign that for later:

the_mat <- do.call(rbind, lapply(dat3, function(x) do.call(rbind, x)))

#============================================    
# Now we put it all together with data.frame:

data.frame(ID, the_mat)

R: split string & assign variable based on split

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