Is there anyway to read .dat file from movielens to R studio - r

Question

I am trying to use Import Dataset in R Studio to read ratings.dat from movielens.
Basically it has this format:
1::1::5::978824268
1::1022::5::978300055
1::1028::5::978301777
1::1029::5::978302205
1::1035::5::978301753
So I need to replace :: by : or ' or white spaces, etc. I use notepad++, it helps to load the file quite fast (compare to note) and can view very big file easily. However, when I do replacement, it shows some strange characters:
"LF"
as I do some research here, it said that it is \n (line feed or line break). But I do not know why when it load the file, it do not show these, only when I do replacement then they appear. And when I load into R Studio, it still detect as "LF", not line break and cause error in data reading.
What is the solution for that ? Thank you !
PS: I know there is python code for converting this but I don't want to use it, is there any other ways ?

Answer 1

Try this:
url <- "http://files.grouplens.org/datasets/movielens/ml-10m.zip"
## this part is agonizingly slow
tf <- tempfile()
download.file(url,tf, mode="wb") # download archived movielens data
files <- unzip(tf, exdir=tempdir()) # unzips and returns a vector of file names
ratings <- readLines(files[grepl("ratings.dat$",files)]) # read rating.dat file
ratings <- gsub("::", "\t", ratings)
# this part is much faster
library(data.table)
ratings <- fread(paste(ratings, collapse="\n"), sep="\t")
# Read 10000054 rows and 4 (of 4) columns from 0.219 GB file in 00:00:07
head(ratings)
# V1 V2 V3 V4
# 1: 1 122 5 838985046
# 2: 1 185 5 838983525
# 3: 1 231 5 838983392
# 4: 1 292 5 838983421
# 5: 1 316 5 838983392
# 6: 1 329 5 838983392

Answer 2

Alternatively (use the d/l code from jlhoward but he also updated his code to not use built-in functions and switch to data.table while i wrote this, but mine's still faster/more efficient :-)
library(data.table)
# i try not to use variable names that stomp on function names in base
URL <- "http://files.grouplens.org/datasets/movielens/ml-10m.zip"
# this will be "ml-10m.zip"
fil <- basename(URL)
# this will download to getwd() since you prbly want easy access to
# the files after the machinations. the nice thing about this is
# that it won't re-download the file and waste bandwidth
if (!file.exists(fil)) download.file(URL, fil)
# this will create the "ml-10M100K" dir in getwd(). if using
# R 3.2+ you can do a dir.exists() test to avoid re-doing the unzip
# (which is useful for large archives or archives compressed with a
# more CPU-intensive algorithm)
unzip(fil)
# fast read and slicing of the input
# fread will only spit on a single delimiter so the initial fread
# will create a few blank columns. the [] expression filters those
# out. the "with=FALSE" is part of the data.table inanity
mov <- fread("ml-10M100K/ratings.dat", sep=":")[, c(1,3,5,7), with=FALSE]
# saner column names, set efficiently via data.table::setnames
setnames(mov, c("user_id", "movie_id", "tag", "timestamp"))
mov
## user_id movie_id tag timestamp
## 1: 1 122 5 838985046
## 2: 1 185 5 838983525
## 3: 1 231 5 838983392
## 4: 1 292 5 838983421
## 5: 1 316 5 838983392
## ---
## 10000050: 71567 2107 1 912580553
## 10000051: 71567 2126 2 912649143
## 10000052: 71567 2294 5 912577968
## 10000053: 71567 2338 2 912578016
## 10000054: 71567 2384 2 912578173
It's quite a bit faster than built-in functions.

Answer 3

Small improvement to #hrbrmstr's answer:
mov <- fread("ml-10M100K/ratings.dat", sep=":", select=c(1,3,5,7))