Suppose i have a dataframe with 100 rows and 100 columns.
For each row, if any 2 columns have the same value, then this row should be removed.
For example, if column 1 and 2 are equal, then this row should be removed.
Another example, if column 10 and column 47 are equal, then this row should be removed as well.
Example:
test <- data.frame(x1 = c('a', 'a', 'c', 'd'),
x2 = c('a', 'x', 'f', 'h'),
x3 = c('s', 'a', 'f', 'g'),
x4 = c('a', 'x', 'u', 'a'))
test
x1 x2 x3 x4
1 a a s a
2 a x a x
3 c f f u
4 d h g a
Only the 4th row should be kept.
How to do this in a quick and concise way? Not using for loops....
Use apply to look for duplicates in each row. (Note that this internally converts your data to a matrix for the comparison. If you are doing a lot of row-wise operations I would recommend either keeping it as a matrix or converting it to a long format as in Jack Brookes's answer.)
# sample data
set.seed(47)
dd = data.frame(matrix(sample(1:5000, size = 100^2, replace = TRUE), nrow = 100))
# remove rows with duplicate entries
result = dd[apply(dd, MARGIN = 1, FUN = function(x) !any(duplicated(x))), ]