bgg
bgg

Reputation: 131

Tranpose and Calculate pearson correlation

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?

Upvotes: 3

Views: 529

Answers (2)

jay.sf
jay.sf

Reputation: 72693

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")

Upvotes: 2

Niek
Niek

Reputation: 1624

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

Upvotes: 2

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