Can I subset rows that have a mix of NA and non NA?-CodePudding

Hello I am trying to take a DF columns 13:19 and return all rows that contain at least one piece of data. DF could look like:

13    14       15... 19
cool  not cool NA...
NA    NA  NA   NA...
NA    1   NA   NA...
NA    NA  NA   NA...

and return just

13    14       15... 19
cool  not cool NA...
NA    1   NA   NA...

I have tried variants of:

df %>% select(c(13:19)) %>% !is.na()

na.omit(df[,c(13:19)])

df[,c(13:19)] %>% 
  select_if(~ !any(is.na(.)))

I would love to be able to do this with dplyr but cannot.

I think what I am passing is trying to parse TRUE/FALSE on all row data for all columns 13:19 to satisfy the condition of not NA or contains at least 1 or more values. Any help would be greatly appreciated - thank you.

CodePudding user response：

With dplyr, we could look for any rows that do not have NAs and then return only those rows.

library(dplyr)

df %>% 
  filter(if_any(13:19, ~ !is.na(.)))

Or you can use rowSums:

df %>% 
  filter(rowSums(!is.na(df[, c(13:19)])) != 0)

Or in base R:

df[apply(!is.na(df[,13:19]),1,any),]

df[rowSums(!is.na(df[,13:19])) != 0,]