r - Use group_by to filter specific cases while keeping NAs -

i want filter dataset keep cases observations in specific column. illustrate:

help <- data.frame(deid = c(5, 5, 5, 5, 5, 12, 12, 12, 12, 17, 17, 17),                score.a = c(na, 1, 1, 1, na, na, na, na, na, na, 1, na)) 

creates

   deid score.a 1     5      na 2     5       1 3     5       1 4     5       1 5     5      na 6    12      na 7    12      na 8    12      na 9    12      na 10   17      na 11   17       1 12   17      na 

and want tell dplyr keep cases have observations in score.a, including na values. thus, want return:

  deid score.a 1     5      na 2     5       1 3     5       1 4     5       1 5     5      na 6    17      na 7    17       1 8    17      na 

i ran code help %>% group_by(deid) %>% filter(score.a > 0) pulls out nas well. thank assistance.

edit: similar question asked here how remove groups of observation dplyr::filter() however, in answer use 'all' condition , requires use of 'any' condition.

try

library(dplyr) %>%       group_by(deid) %>%       filter(any(score.a >0 & !is.na(score.a))) #    deid score.a #1    5      na #2    5       1 #3    5       1 #4    5       1 #5    5      na #6   17      na #7   17       1 #8   17      na 

or similar approach data.table

library(data.table) setdt(help)[, if(any(score.a>0 & !is.na(score.a))) .sd , deid] #    deid score.a #1:    5      na #2:    5       1 #3:    5       1 #4:    5       1 #5:    5      na #6:   17      na #7:   17       1 #8:   17      na 

if condition subset 'deid's values in 'score.a' > 0, above code can modified to,

setdt(help)[,  if(!all(is.na(score.a)) &           all(score.a[!is.na(score.a)]>0)) .sd , deid] #   deid score.a #1:    5      na #2:    5       1 #3:    5       1 #4:    5       1 #5:    5      na #6:   17      na #7:   17       1 #8:   17      na 

suppose 1 of 'score.a' in 'deid' group less 0,

help$score.a[3] <- -1 

the above code return

 setdt(help)[,  if(!all(is.na(score.a)) &             all(score.a[!is.na(score.a)]>0, deid],  #   deid score.a  #1:   17      na  #2:   17       1  #3:   17      na