User Based Recommendation in R - r

Question

I am trying to do user based recommendation in R by using recommenderlab package but all the time I am getting 0(no) prediction out of the model.
my code is :
library("recommenderlab")
# Loading to pre-computed affinity data
movie_data<-read.csv("D:/course/Colaborative filtering/data/UUCF Assignment Spreadsheet_user_row.csv")
movie_data[is.na(movie_data)] <- 0
rownames(movie_data) <- movie_data$X
movie_data$X <- NULL
# Convert it as a matrix
R<-as.matrix(movie_data)
# Convert R into realRatingMatrix data structure
# realRatingMatrix is a recommenderlab sparse-matrix like data-structure
r <- as(R, "realRatingMatrix")
r
rec=Recommender(r[1:nrow(r)],method="UBCF", param=list(normalize = "Z-score",method="Cosine",nn=5, minRating=1))
recom <- predict(rec, r["1648"], n=5)
recom
as(recom, "list")
all the time I am getting out put like :
as(recom, "list")
$`1648`
character(0)
I am using user-row data from this link:
https://drive.google.com/file/d/0BxANCLmMqAyIQ0ZWSy1KNUI4RWc/view
In that data column A contains user id and apart from that all are movie rating for each movie name.
Thanks.

Answer 1

The line of code movie_data[is.na(movie_data)] <- 0 is the source of the error. For realRatingMatrix (unlike the binaryRatingMatrix) the movies that are not rated by the users are expected to be NA values, not zero values. For example, the following code gives the correct predictions:
library("recommenderlab")
movie_data<-read.csv("UUCF Assignment Spreadsheet_user_row.csv")
rownames(movie_data) <- movie_data$X
movie_data$X <- NULL
R<-as.matrix(movie_data)
r <- as(R, "realRatingMatrix")
rec=Recommender(r,method="UBCF", param=list(normalize = "Z-score",method="Cosine",nn=5, minRating=1))
recom <- predict(rec, r["1648"], n=5)
as(recom, "list")
# [[1]]
# [1] "X13..Forrest.Gump..1994." "X550..Fight.Club..1999."
# [3] "X77..Memento..2000." "X122..The.Lord.of.the.Rings..The.Return.of.the.King..2003."
# [5] "X1572..Die.Hard..With.a.Vengeance..1995."