r - Selecting and filtering on the same variables in dplyr -

let's have matrix 3 columns , 100 rows. let column names a_dem, b_dem , c_blah. , let's imagine each cell can have value between 0 , 100.

is there way use select(), filter() , %>% select observations end "_dem" , have value larger than, say, 50?

i would've kinda imagined along these lines:

dat %>%      select(ends_with("dem")) %>%         filter(>50) %>%             summary() 

but doesn't work, obviously.

so, there way kind of selection , filtering, or have resort more complicated?

you this:

library(dplyr) set.seed(2)  a_dem <- runif(100,0,100) b_dem <- runif(100,0,100) c_blah <- runif(100,0,100)  dat <- data.frame(a_dem, b_dem, c_blah)  newdat1 <- dat %>% select(ends_with("_dem"))  filtered <- sapply(newdat1, function(x) ifelse(x>50, x, na))  >head(filtered)          a_dem    b_dem [1,]       na       na [2,] 70.23740       na [3,] 57.33263 98.06000 [4,]       na 82.89221 [5,] 94.38393       na [6,] 94.34750 59.59169 

and depending on want next exclude na values.

---

update:

to in dplyr can use method linked here @sgp667

newdat2 <- dat %>%    select(ends_with("_dem")) %>%    mutate_each(funs(((function(x){ifelse(x>50, x, na)})(.))))  > head(newdat2)      a_dem    b_dem 1       na       na 2 70.23740       na 3 57.33263 98.06000 4       na 82.89221 5 94.38393       na 6 94.34750 59.59169