R: remove duplicate values in different rows and columns
I found many pages about finding duplicate items in a list or duplicate rows in a dataframe. However, I want to search for duplicated elements throughout the dataframe. Let's take this as an example:
df
coupon1 coupon2 coupon3
1 10 11 12
2 13 16 15
3 16 17 18
4 19 20 21
5 22 23 24
6 25 26 27
You will notice that df [2,2] and df [3,1] have the same element (16). When I ran
duplicated(df)
It returns six "FALSE" because the entire string is not duplicated, only one element. How do I check for any duplicate values in the entire dataframe? I would like to know that a duplicate exists and also to know its value (and the same if there are multiple duplicates).
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This will find global spoofs, but it will search by column. So, (3,1) will still be FALSE since it is the first value 16
in the data frame.
m <- matrix(duplicated(unlist(df)), ncol=ncol(df))
# [,1] [,2] [,3]
#[1,] FALSE FALSE FALSE
#[2,] FALSE TRUE FALSE
#[3,] FALSE FALSE FALSE
#[4,] FALSE FALSE FALSE
#[5,] FALSE FALSE FALSE
#[6,] FALSE FALSE FALSE
Then you can use it but want, for example:
df[m]
#[1] 16
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