Tranpose and Calculate pearson correlation - r

Question

I am really new to coding and I need to run a number of statistics in a dataset, for example the pearson correlation, but I am having some trouble manipulating the data.
From what I understood I need to transpose my data in order to calculate the pearson correlation, but here's where I'm having some problems. For starters, the column names turn into a new row instead of becoming the new column names. Then I get a message that my values are not numeric.
I also have some NA and I am trying to calculate the correlation with this code
cor(cr, use = "complete.obs", method = "pearson")
Error in cor(cr1, use = "complete.obs", method = "pearson") :
'x' must be numeric
I need to know the correlation between Victoria and Nuria which should yield 0.3651484
here is the dput of my dataset:
> dput(cr)
structure(list(User = structure(c(8L, 10L, 2L, 17L, 11L, 1L,
18L, 9L, 7L, 5L, 3L, 14L, 13L, 4L, 20L, 6L, 16L, 12L, 15L, 19L
), .Label = c("Ana", "Anton", "Bernard", "Carles", "Chris", "Ivan",
"Jim", "John", "Marc", "Maria", "Martina", "Nadia", "Nerea",
"Nuria", "Oriol", "Rachel", "Roger", "Sergi", "Valery", "Victoria"
), class = "factor"), Star.Wars.IV...A.New.Hope = c(1L, 5L, NA,
NA, 4L, 2L, NA, 4L, 5L, 4L, 2L, 3L, 2L, 3L, 4L, NA, NA, 4L, 5L,
1L), Star.Wars.VI...Return.of.the.Jedi = c(5L, 3L, NA, 3L, 3L,
4L, NA, NA, 1L, 2L, 1L, 5L, 3L, NA, 4L, NA, NA, 5L, 1L, 2L),
Forrest.Gump = c(2L, NA, NA, NA, 4L, 4L, 3L, NA, NA, NA,
5L, 2L, NA, 3L, NA, 1L, NA, 1L, NA, 2L), The.Shawshank.Redemption = c(NA,
2L, 5L, NA, 1L, 4L, 1L, NA, 4L, 5L, NA, NA, 5L, NA, NA, NA,
NA, 5L, NA, 4L), The.Silence.of.the.Lambs = c(4L, 4L, 2L,
NA, 4L, NA, 1L, 3L, 2L, 3L, NA, 2L, 4L, 2L, 5L, 3L, 4L, 1L,
NA, 5L), Gladiator = c(4L, 2L, NA, 1L, 1L, NA, 4L, 2L, 4L,
NA, 5L, NA, NA, NA, 5L, 2L, NA, 1L, 4L, NA), Toy.Story = c(2L,
1L, 4L, 2L, NA, 3L, NA, 2L, 4L, 4L, 5L, 2L, 4L, 3L, 2L, NA,
2L, 4L, 2L, 2L), Saving.Private.Ryan = c(2L, NA, NA, 3L,
4L, 1L, 5L, NA, 4L, 3L, NA, NA, 5L, NA, NA, 2L, NA, NA, 1L,
3L), Pulp.Fiction = c(NA, NA, NA, 4L, NA, 4L, 2L, 3L, NA,
4L, NA, 1L, NA, NA, 3L, NA, 2L, 5L, 3L, 2L), Stand.by.Me = c(3L,
4L, 1L, NA, 1L, 4L, NA, NA, 1L, NA, NA, NA, NA, 4L, 5L, 1L,
NA, NA, 3L, 2L), Shakespeare.in.Love = c(2L, 3L, NA, NA,
5L, 5L, 1L, NA, 2L, NA, NA, 3L, NA, NA, NA, 5L, 2L, NA, 3L,
1L), Total.Recall = c(NA, 2L, 1L, 4L, 1L, 2L, NA, 2L, 3L,
NA, 3L, NA, 2L, 1L, 1L, NA, NA, NA, 1L, NA), Independence.Day = c(5L,
2L, 4L, 1L, NA, 4L, NA, 3L, 1L, 2L, 2L, 3L, 4L, 2L, 3L, NA,
NA, NA, NA, NA), Blade.Runner = c(2L, NA, 4L, 3L, 4L, NA,
3L, 2L, NA, NA, NA, NA, NA, 2L, NA, NA, NA, 4L, NA, 5L),
Groundhog.Day = c(NA, 2L, 1L, 5L, NA, 1L, NA, 4L, 5L, NA,
NA, 2L, 3L, 3L, 2L, 5L, NA, NA, NA, 5L), The.Matrix = c(4L,
NA, 1L, NA, 3L, NA, 1L, NA, NA, 2L, 1L, 5L, NA, 5L, NA, 2L,
4L, NA, 2L, 4L), Schindler.s.List = c(2L, 5L, 2L, 5L, 5L,
NA, NA, 1L, NA, 5L, NA, NA, NA, 1L, 3L, 2L, NA, 2L, NA, 3L
), The.Sixth.Sense = c(5L, 1L, 3L, 1L, 5L, 3L, NA, 3L, NA,
1L, 2L, NA, NA, NA, NA, 4L, NA, 1L, NA, 5L), Raiders.of.the.Lost.Ark = c(NA,
3L, 1L, 1L, NA, NA, 5L, 5L, NA, NA, 1L, NA, 5L, NA, 3L, 3L,
NA, 2L, NA, 3L), Babe = c(NA, NA, 3L, 2L, NA, 2L, 2L, NA,
5L, NA, 4L, 2L, NA, NA, 1L, 4L, NA, 5L, NA, NA)), .Names = c("User",
"Star.Wars.IV...A.New.Hope", "Star.Wars.VI...Return.of.the.Jedi",
"Forrest.Gump", "The.Shawshank.Redemption", "The.Silence.of.the.Lambs",
"Gladiator", "Toy.Story", "Saving.Private.Ryan", "Pulp.Fiction",
"Stand.by.Me", "Shakespeare.in.Love", "Total.Recall", "Independence.Day",
"Blade.Runner", "Groundhog.Day", "The.Matrix", "Schindler.s.List",
"The.Sixth.Sense", "Raiders.of.the.Lost.Ark", "Babe"), row.names = c(NA,
-20L), class = c("tbl_df", "tbl", "data.frame"))
Can someone help me?

Answer 1

This code should give you the correlation matrix between all users.
cr2<-t(cr[,2:21]) # Transpose (first column contains names)
colnames(cr2)<-cr[,1] # Assign names to columns
cor(cr2,use="complete.obs") # Gives an error because there are no complete obs
# Error in cor(cr2, use = "complete.obs") : no complete element pairs
cor(cr2,use="pairwise.complete.obs") # use pairwise deletion
Correlation between Victoria and Nuria is 0.36514837 (using pairwise deletion)
Edit:To get just the correlation between Victoria and Nuria with listwise deletion, run the above and then
cr2<-as.data.frame(cr2)
with(cr2, cor(Victoria, Nuria, use = "complete.obs", method = "pearson"))
[1] 0.3651484

Answer 2

As a summary in addition to #Niek's answer. First transpose the data frame by t() by excluding first column (which contains the names and is not numeric and thus cannot used for correlation calculations); assign these names to new columns in same step. Then calculate specific correlations. The solution in one piece would be:
cr2 <- setNames(as.data.frame(t(cr[, -1])), cr[, 1])
with(cr2, cor(Victoria, Nuria, use = "complete.obs"))
[1] 0.3651484
Or for the whole correlation matrix:
cor(cr2, use = "pairwise.complete.obs")