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Count occurrences of specific words from a dataframe row in R

I have a Dataset with 2 columns and multiple rows. first column ID, second column the text which belongs to it.

I want to add more columns which sums up how many times a certain string appears in the text from the Row. the string would be "\\n Positive\\n", "\\n Neutral\\n", "\\n Negativ\\n"`

Example of the Dataset:

Id, Content
2356, I like cheese.\n  Positive\nI don't want to be here.\n Negative\n
3456, I am alone.\n Neutral\n

At the End it should look like

Id, Content,Positiv, Neutral, Negativ
2356, I like cheese.\n  Positive\nI don't want to be here.\n Negative\n,1 ,0 ,1
3456, I am alone.\n Neutral\n, 0, 1, 0

Right now i tried it like this but it isn't giving the right answers:

getCount1 <- function(data, keyword)
{
Positive <- str_count(Dataset$CONTENT, keyword)
return(data.frame(data,Positive))
}
Stufe1 <-getCount1(Dataset,'\n Positive\n')
################################################################
getCount2 <- function(data,  keyword)
{
Neutral <- str_count(Stufe1$CONTENT, keyword)
return(data.frame(data,Neutral))
}
Stufe2 <-getCount2(Stufe1,'\n  Neutral\n')
#####################################################
getCount3 <- function(data,  keyword)
{
Negative <- str_count(Stufe2$CONTENT, keyword)
return(data.frame(data,Negative))
}
Stufe3 <-getCount3(Stufe2,'\n  Negative\n')

I Assume this is what you require

Sample data

id <- c(1:4)
text <- c('I have a Dataset with 2 columns a',
          'nd multiple rows. first column ID', 'second column the text which',
          'n the text which belongs to it.')
dataset <- data.frame(id,text)

Function to find count

library(stringr)
getCount <- function(data,keyword)
{
  wcount <- str_count(dataset$text, keyword)
  return(data.frame(data,wcount))
}

Calling getCount should give the updated dataset

> getCount(dataset,'second')
  id                              text wcount
  1   I have a Dataset with 2 columns a      0
  2   nd multiple rows. first column ID      0
  3        second column the text which      1
  4     n the text which belongs to it.      0

To offer some alternatives, let's start with a slightly modified version of @on_the_shores_of_linux_sea's dataset.

id <- c(1:4)
text <- c('I have a Dataset with 2 columns a',
          'nd multiple rows. first column ID rows', 
          'second column the text which',
          'n the text which belongs to it.')
dataset <- data.frame(id,text)

Sticking with base R functions, you could come up with a function like this one.

wordCounter <- function(invec, word, ...) {
  vapply(regmatches(invec, gregexpr(word, invec, ...)), length, 1L)
}

You would use it like this:

## allows other arguments to gregexpr
wordCounter(dataset$text, "id", ignore.case = TRUE) 
# [1] 0 1 0 0
wordCounter(dataset$text, "id")
# [1] 0 0 0 0
wordCounter(dataset$text, "rows")
# [1] 0 2 0 0
wordCounter(dataset$text, "second", ignore.case = TRUE)
# [1] 0 0 1 0

Another alternative, if you want to go with some ready-made solutions, would be to use the "stringi" package, which has a nifty stri_count* set of functions. Here, I've used stri_count_fixed :

library(stringi)
stri_count_fixed(dataset$text, "rows")
# [1] 0 2 0 0

This can also be done without loading any additional library, as pointed out by Ananda. My solution would be, provided that the 2-column table is called dataset and the string to look for is mystring :

countOccurr = function(text,motif) {
 res = gregexpr(motif,text,fixed=T)[[1]]
 ifelse(res[1] == -1, 0, length(res))
}

dataset = cbind(dataset, count = vapply(dataset[,2], countOccurr, 1, motif=mystring))

Beware that the second column of your dataframe has to be of mode character if you want to avoid problems (the dataframe given as sample data by @on-the-shores-of-linux-sea retains mode factor, which is fine with his solution but not with mine). Otherwise use as.character(dataset[,2]) to cast.

Why not just:

dataset$Positiv <- str_count(dataset$Content, 'Positiv')
dataset$Neutral <- str_count(dataset$Content, 'Neutral')
dataset$Negativ <- str_count(dataset$Content, 'Negativ')

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