CODEWITHSUNDEEP
rtwittersentiment-analysis
user3588494
user3588494

Reputation: 13

nested for-loop in R language

I have this code to calculate duplicate in a data frame using cosine similarity through firstly: first loop (nrow) times to take in each time one tweet then compares the cosine similarity results to this tweet with other tweets using second loop.

Here is my code:

for (i in 1:nrow(temp)) {
  dup=0
  one_Tweets = tweets$Tweet[i]
  cos_similarity = data.frame("v1"=NULL) # NULL So that don't write previous value
  cos_similarity=data.frame(sim <- round( sim.strings(AllTweets,one_Tweets), digits = 3) )
  names(cos_similarity) = c( "v1")

  for (b in i+1:nrow(temp)) {
    Tweet_cos=cos_similarity$v1[b]
    if ( Tweet_cos >= 0.900) {
      count = count+1
      tweets$flag[b]= 1
    }else { #if ( Tweet_cos <0.900) {
      tweets$flag[b]= 2
    }
    Tweet_cos=0
  }
  dup=tweets$duplicate[i]= tweets$duplicate[i]+count 
  count = 0
}

I have a problem in first loop, entered one time although that number of tweets in data frame 10000 tweets.

and i get the error:

Error in if (Tweet_cos >= 0.9) { : missing value where TRUE/FALSE needed

Upvotes: 1

Views: 101

Answers (1)

abhiieor
abhiieor

Reputation: 3554

I dont still have rep to put it in comment but I think you are getting this problem because of NA/NULL in Tweet_cos vector. to debug remove this part from code:

    for (b in i+1:nrow(temp)) {
    Tweet_cos=cos_similarity$v1[b]
    if ( Tweet_cos >= 0.900) {
      count = count+1
      tweets$flag[b]= 1
    }else { #if ( Tweet_cos <0.900) {
      tweets$flag[b]= 2
    }
    Tweet_cos=0
  }
  dup=tweets$duplicate[i]= tweets$duplicate[i]+count 
  count = 0

replace whole of this with print(cos_similarity$v1). You should ideally see some NA/NULL which by def could not be compared with 0.9 and hence the error.

If there are too many iterations/loop then try to print values of i and b where you are getting error and print cos_similarity$v1 only for that.

Please consider sharing small sample data so that others can replicate your problem

Upvotes: 0

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