Hi! I have a question regarding this dataset that I have.
x = list(a = c(3,4,5), b = list(b1 = 10:13, b2 = 11:14, b3 = 12:15), c = list(c1 = c(1,2,NA,4), c2 = c(1,2,NA,5), c3 = c(1,2,NA,6))) df <- x %>% as_tibble()
The goal is to filter the NA from column C and showing which value belongs in column B. This may be a silly question, however, my real dataset has - as the column C in this regrex - an integer list with 1800 values in it and almost 250 columns B following the same logic.
Please, any comment that you can tell me will be highly appreciated.
PS. I know that there are NA in this column C by doing this
df %>% mutate(d = map_int(c, ~sum(is.na(.))))
However, I just no only need how much NA there are, I require to know which data from the other column is associated with. The final result must be looks like this
df_expected <- tibble( a = c(3,4,5), b = c(12,13,14), c = c(NA, NA, NA) )