dplyr - counting a number of specific values in each column - for all columns at once

Well, dplyr seems a bit of overkill as it's so simple with plain old
vapply() in base R :

dat <- data.frame (a=sample(1:5,10,rep=TRUE),

+                    b=sample(3:7,10,rep=TRUE),
+                    g = sample(7:9,10,rep=TRUE))

vapply(dat,function(x)sum(x==5,na.rm=TRUE),1L)

a b g
5 4 0



Cheers,
Bert

Bert Gunter

"Data is not information. Information is not knowledge. And knowledge is
certainly not wisdom."
   -- Clifford Stoll

On Tue, Jun 16, 2015 at 10:24 AM, Dimitri Liakhovitski
<dimitri.liakhovitski at gmail.com> wrote:

Hello!

I have a data frame:

md <- data.frame(a = c(3,5,4,5,3,5), b = c(5,5,5,4,4,1), c =
c(1,3,4,3,5,5),
      device = c(1,1,2,2,3,3))
myvars = c("a", "b", "c")
md[2,3] <- NA
md[4,1] <- NA
md

I want to count number of 5s in each column - by device. I can do it like
this:

library(dplyr)
group_by(md, device) %>%
summarise(counts.a = sum(a==5, na.rm = T),
          counts.b = sum(b==5, na.rm = T),
          counts.c = sum(c==5, na.rm = T))

However, in real life I'll have tons of variables (the length of
'myvars' can be very large) - so that I can't specify those counts.a,
counts.b, etc. manually - dozens of times.

Does dplyr allow to run the count of 5s on all 'myvars' columns at once?


--
Dimitri Liakhovitski