Recognize patterns in column, and add them to column in Data frame

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Got a column with 50 keywords:

Keyword1 
Keyword2
Keyword3
KeywordN=50

In addition I got a data frame with two columns: Title and Abstract.

Title                    Abstract 
Rstudio Keyword1        A interesting program language keyword2  
Python Keyword3         A interesting program keyword3 language 

I want to get an extra column (let's call it Keywords), where the keyword name will appear IF it is in the Title or Abstract, like this:

Title             Abstract                                   Keywords
Rstudio Keyword1 A interesting program language keyword2  Keyword1, keyword2
Python Keyword2  A interesting program keyword3 language  Keyword2, Keyword3

The only thing how I could 'solve' this, was by making a binary columns (if a pattern matched). (grepl function), but that was not the desired solution...

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cbind(dat,Keywords=do.call(paste,c(sep=",",Map(sub,paste0(".*(",paste(keywords,collapse="|"),").*"),"\\1",dat,TRUE))))
             Title                                Abstract          Keywords
1 Rstudio Keyword1 A interesting program language keyword2 Keyword1,keyword2
2  Python Keyword3 A interesting program keyword3 language Keyword3,keyword3

where keywords=paste0("Keyword",1:3) and

dat=read.table(text="Title                    Abstract 
'Rstudio Keyword1'        'A interesting program language keyword2'  
'Python Keyword3'         'A interesting program keyword3 language'",h=T,strin=F)

The line might seem long: Breakdown:

a=paste0(".*(",paste(keywords,collapse="|"),").*")
b=do.call(paste,c(sep=",",Map(sub,a,"\\1",dat,TRUE)))
cbind(dat,keywords=b)
             Title                                Abstract          keywords
1 Rstudio Keyword1 A interesting program language keyword2 Keyword1,keyword2
2  Python Keyword3 A interesting program keyword3 language Keyword3,keyword3

Tutorial: Python Regex (Regular Expressions) for Data Scientists, Regular expressions (regex) are essentially text patterns that you can use to By adding a . next to From: , we look for one additional character next to it. Each of these categories will become a column in our pandas dataframe (i.e., our  As with a matrix, a data frame can be accessed by row and column with [,]. One difference is that if we try to get a single row of the data frame, we get back a data frame with one row, rather than a vector. This is because the row may contain data of different types, and a vector can only hold elements of all the same type.

Another approach using strsplit (also in base R):

ls <- strsplit(tolower(paste(df$Title, df$Abstract)), 
                       "(\\s+)|(?!')(?=[[:punct:]])", perl = TRUE)    

df$Keywords <- do.call("rbind", 
               lapply(ls, function(x) paste(unique(x[x %in% tolower(keywords)]), 
               collapse = ", ")))

#             Title                                Abstract           Keywords
#1 Rstudio Keyword1 A interesting program language keyword2 keyword1, keyword2
#2  Python Keyword2 A interesting program keyword3 language keyword2, keyword3
Sample data
df <- data.frame(Title = c("Rstudio Keyword1", "Python Keyword2"), 
                 Abstract = c("A interesting program language keyword2",  
                              "A interesting program keyword3 language"), 
                 stringsAsFactors = F)

keywords <- paste0("Keyword", 1:4)

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Title<-as.character(c("Rstudio Keyword1","Python Keyword3"))
Abstract<-as.character(c("A interesting program language keyword2"," A interesting program keyword3 language"))
example1.data <- data.frame(Title,Abstract)


#loop answer
f<-length(example1.data)
example1.data$Keyword <- NA

for (i in 1:nrow(example1.data)){
testA[i]<-regmatches(example1.data$Title[i], regexpr("(Keyword|keyword) ([0-9])", example1.data$Title[i]))
testB[i]<-regmatches(example1.data$Abstract[i], regexpr("(Keyword|keyword)([0-9])", example1.data$Abstract[i]))
example1.data$Keyword[i]<-paste(testA[i],testB[i],  sep=", ")

}

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Comments
  • updated as it failed with data from modified question
  • > ind2 <- do.call(rbind,Map(data.frame,keyword=keywords1,i=ind)) Error in (function (..., row.names = NULL, check.rows = FALSE, check.names = TRUE, : arguments imply differing number of rows: 1, 0
  • it works fine for me... and it's all base R... can someone else replicate the issue ?
  • It's not my code in any case, I don't use keywords1
  • Correct, keywords1 == keywords in my code :-). So that should not be the difference. (Sorry for the confusion)
  • Solution worked. But is there one more possibility, that you get only unique values? E.g.: if row one consist out of: keyword1,keyword1 and keyword1, then the result will be: "keyword1", "keyword1", keyword1". Ideally would be one time: "keyword1" (so unique values per row)
  • it fails if the keyword happens after a punctuation character
  • also fails if the keyword includes a space
  • @Moody_Mudskipper I made an edit for the punctuation issue.
  • Thanks, but: df$Keywords <- do.call("rbind", lapply(ls, function(x) paste(unique(x[x %in% tolower(keywords))], collapse = ", "))) Contains some error (I guess with the brackets)