I have a different problem that I have not encountered yet. When I try to make a completely reproducible example, I get errors, so I am posting what my data look like, and what I would like it to look like. I am asking for suggestions on how to get the data into the shape I need to do some analyses.
Here is what the data look like:
If I am breaking some type of protocol, I apologize. When I try to make a reproducible example, I get the following error: "Error in [<-.data.frame(*tmp*, 2, 3, value = 3) :
new columns would leave holes after existing columns" This is the best I can do for some help.
I have tried binding rows, deleting rows with NAs, na.omit(), and several others. I just need to get the data to where it is no longer 7 columns and 9 rows, but to 7 columns and 3 rows.
Thank you
>Solution :
We may loop across columns other than index, order based on the NA elements so that all non-NAs order at the top followed by NA and then use filter to remove the rows having all NAs with if_any
library(dplyr)
df1 %>%
mutate(across(-index, ~ .x[order(is.na(.x))])) %>%
filter(if_any(-index, complete.cases))
NOTE: This will keep some NA rows in case there are difference in number of NAs per each columns