You need %in% instead of ==:
library(dplyr)
target <- c("Tom", "Lynn")
filter(dat, name %in% target) # equivalently, dat %>% filter(name %in% target)
Produces
days name
1 88 Lynn
2 11 Tom
3 1 Tom
4 222 Lynn
5 2 Lynn
To understand why, consider what happens here:
dat$name == target
# [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE
Basically, we're recycling the two length target vector four times to match the length of dat$name. In other words, we are doing:
Lynn == Tom
Tom == Lynn
Chris == Tom
Lisa == Lynn
... continue repeating Tom and Lynn until end of data frame
In this case we don't get an error because I suspect your data frame actually has a different number of rows that don't allow recycling, but the sample you provide does (8 rows). If the sample had had an odd number of rows I would have gotten the same error as you. But even when recycling works, this is clearly not what you want. Basically, the statement dat$name == target is equivalent to saying:
return
TRUEfor every odd value that is equal to "Tom" or every even value that is equal to "Lynn".
It so happens that the last value in your sample data frame is even and equal to "Lynn", hence the one TRUE above.
To contrast, dat$name %in% target says:
for each value in
dat$name, check that it exists intarget.
Very different. Here is the result:
[1] TRUE TRUE FALSE FALSE FALSE TRUE TRUE TRUE
Note your problem has nothing to do with dplyr, just the mis-use of ==.