CODEWITHSUNDEEP
rdplyr
b222
b222

Reputation: 976

Use group_by to filter specific cases while keeping NAs

I want to filter my dataset to keep cases with observations in a specific column. To 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 I want to tell dplyr to keep cases that have any observations in score.a, including the NA values. Thus, I want it to 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 the code help %>% group_by(deid) %>% filter(score.a > 0) however it pulls out the NAs as well. Thank you for any assistance.

Edit: A similar question was asked here How to remove groups of observation with dplyr::filter() However, in the answer they use the 'all' condition and this requires use of the 'any' condition.

Upvotes: 2

Views: 1039

Answers (2)

Shenglin Chen
Shenglin Chen

Reputation: 4554

library(dplyr)
df%>%group_by(deid)%>%filter(sum(score.a,na.rm=T)>0)

Upvotes: 2

akrun
akrun

Reputation: 887078

Try

library(dplyr)
help %>%
      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 a similar approach with 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 the condition is to subset 'deid's with all the values in 'score.a' > 0, then the above code can be 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 one of the 'score.a' in 'deid' group is less than 0, 

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

the above code would 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

Upvotes: 5

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