Remove group from data.frame if at least one group member meets condition

Question

I have a `data.frame` where I'd like to remove entire groups if any of their members meets a condition. In this first example, if the values are numbers and the condition is `NA` the code below works. ``` df <- structure(list(world = c(1, 2, 3, 3, 2, NA, 1, 2, 3, 2), place = c(1, 1, 2, 2, 3, 3, 1, 2, 3, 1), group = c(1, 1, 1, 2, 2, 2, 3, 3, 3, 3)), .Names = c("world", "place", "group"), row.names = c(NA, -10L), class = "data.frame") ans <- ddply(df, . (group), summarize, code=mean(world)) ans$code[is.na(ans$code)] <- 0 ans2 <- merge(df,ans) final.ans <- ans2[ans2$code !=0,] ``` However, this `ddply` maneuver with the `NA` values will not work if the condition is something other than "`NA`", or if the value are non-numeric. For example, if I wanted to remove groups which have one or more rows with a world value of `AF` (as in the data frame below) this `ddply` trick would not work. ``` df2 <-structure(list(world = structure(c(1L, 2L, 3L, 3L, 3L, 5L, 1L, 4L, 2L, 4L), .Label = c("AB", "A…

Accepted Answer

Try

```
library(dplyr)
df2 %>%
  group_by(group) %>%
  filter(!any(world == "AF"))
```

Or as per metionned by @akrun:

`setDT(df2)[, if(!any(world == "AF")) .SD, group]`

Or

`setDT(df2)[, if(all(world != "AF")) .SD, group]`

Which gives:

```
#Source: local data frame [7 x 3]
#Groups: group
#
#  world place group
#1    AB     1     1
#2    AC     1     1
#3    AD     2     1
#4    AB     1     3
#5    AE     2     3
#6    AC     3     3
#7    AE     1     3
```

Remove group from data.frame if at least one group member meets condition

Solution

Problem