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Got a geeky interest in music related subjects and simple gaming systems like Dreamcast? I’m sure there are a bunch of people like me in the community. .Q:

How to efficiently identify and remove a “one-off” column from a tibble?

Problem
I want to replace the first row of a data frame with the second row of a data frame that has the same identifier.
What I’ve done
In the past, I have used the following code to replace the first row with the second row of a data frame:
dta % mutate(section1 = nrow(dta) – 1) %>% select(-1))

However, when the first row is actually a column, it’s very inefficient as it attempts to remove every single column from the data frame.
dta % mutate(section1 = nrow(dta) – 1) %>% select(-1))

Question
Is there a way to efficiently replace the first row of a tibble with the second row of a tibble that has the same identifier?
My Attempt
I’ve tried making a copy using the identical() function, and then trying to pass that as a vector into rowid_to_column() to see if it’s perhaps letting me know there is one “special” column in the data frame, and then I try row() on that vector, which attempts to remove all the rows from the data frame.

A:

Use the first row of a tibble to index columns of the tibble.
tibble::rowid_to_column(tib1, -1)
#> section2 section3 section4 section1
#> 1 32 33 34

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