R- work inside text - r

Question

I have a table with text like:
tt<-data.frame(a=c("esta es la unica lista que voy a hacer","esta es la 2da unica"))
I need to keep only the words that have more than 3 characters:
tt<-data.frame(a=c("esta unica lista hacer","esta unica"))
In this case I have no clue of how to do it. I know I have to use nchar and a loop over the table and inside another loop over the words.

Answer 1

Using the data.table package:
library(data.table)
setDT(tt)
tt[,a:=gsub("\\s+"," ",gsub("\\b\\w{1,3}\\b","",a))]
a
1: esta unica lista hacer
2: esta unica
Another option, depending on exactly the output you want, is:
library(data.table) #1.9.5+
tt[,tstrsplit(gsub("\\b\\w{1,3}\\b","",a),split="\\s+")]
V1 V2 V3 V4
1: esta unica lista hacer
2: esta unica NA NA
Edit: After much tussling at the encouragement of #rawr, here is a way to get at the problem more directly (include 4-letter words instead of exclude 3-letter words)
tt[,a:=lapply(regmatches(a, gregexpr('\\b\\w{4,}\\b',a)),paste0,collapse=" ")]

Answer 2

It's not too tricky if you break it into chunks. First use apply to iterate over each row of the data frame. Then for each row, break strings into words, select the long ones, paste back into a string, and return the result:
tt<-data.frame(a=c("esta es la unica lista que voy a hacer","esta es la 2da unica"))
library(stringr)
tt$a <- lapply(tt$a, function(x) {
l <- unlist(str_split(x, " "))
t <- l[which(nchar(l)>3)]
return(paste0(t, collapse=" "))
})

Answer 3

Here is another approach using the qdapRegex package.
library(qdapRegex)
tt <- data.frame(a = c('esta es la unica lista que voy a hacer', 'esta es la 2da unica'))
tt$a <- rm_nchar_words(tt$a, 1, pattern = '\\b\\w{1,3}\\b')
tt
# a
# 1 esta unica lista hacer
# 2 esta unica

Answer 4

Here's a solution using the quanteda package, that tokenizes the texts in your data.frame and removes the tokens whose length is <= 3. Note that I have specified stringsAsFactors = FALSE here in the data.frame() -- although this would work equally fine if you were operating directly on a character vector.
require(quanteda)
tt <- data.frame(a=c("esta es la unica lista que voy a hacer", "esta es la 2da unica"),
stringsAsFactors = FALSE)
ttTokenized <- tokenize(tt$a)
(ttTokenized <- sapply(ttTokenized, function(x) x[nchar(x) > 3]))
## [[1]]
## [1] "esta" "unica" "lista" "hacer"
##
## [[2]]
## [1] "esta" "unica"
If you want the original-looking texts rather than the tokenised versions, then use this additional step:
sapply(ttTokenized, paste, collapse = " ")
## [1] "esta unica lista hacer" "esta unica"