Count number of rows by group using dplyr

I am using the mtcars dataset. I want to find the number of records for a particular combination of data. Something very similar to the count(*) group by clause in SQL. ddply() from plyr is working for me

library(plyr)
ddply(mtcars, .(cyl,gear),nrow)

has output

  cyl gear V1
1   4    3  1
2   4    4  8
3   4    5  2
4   6    3  2
5   6    4  4
6   6    5  1
7   8    3 12
8   8    5  2

Using this code

library(dplyr)
g <- group_by(mtcars, cyl, gear)
summarise(g, length(gear))

has output

  length(cyl)
1          32

I found various functions to pass in to summarise() but none seem to work for me. One function I found is sum(G), which returned

Error in eval(expr, envir, enclos) : object 'G' not found

Tried using n(), which returned

Error in n() : This function should not be called directly

What am I doing wrong? How can I get group_by() / summarise() to work for me?

There's a special function n() in dplyr to count rows (potentially within groups):

library(dplyr)
mtcars %>% 
  group_by(cyl, gear) %>% 
  summarise(n = n())
#Source: local data frame [8 x 3]
#Groups: cyl [?]
#
#    cyl  gear     n
#  (dbl) (dbl) (int)
#1     4     3     1
#2     4     4     8
#3     4     5     2
#4     6     3     2
#5     6     4     4
#6     6     5     1
#7     8     3    12
#8     8     5     2

But dplyr also offers a handy count function which does exactly the same with less typing:

count(mtcars, cyl, gear)          # or mtcars %>% count(cyl, gear)
#Source: local data frame [8 x 3]
#Groups: cyl [?]
#
#    cyl  gear     n
#  (dbl) (dbl) (int)
#1     4     3     1
#2     4     4     8
#3     4     5     2
#4     6     3     2
#5     6     4     4
#6     6     5     1
#7     8     3    12
#8     8     5     2

another approach is to use the double colons:

mtcars %>% 
  dplyr::group_by(cyl, gear) %>%
  dplyr::summarise(length(gear))

I think what you are looking for is as follows.

cars_by_cylinders_gears <- mtcars %>%
  group_by(cyl, gear) %>%
  summarise(count = n())

This is using the dplyr package. This is essentially the longhand version of the count () solution provided by docendo discimus.

Another option, not necesarily more elegant, but does not require to refer to a specific column:

mtcars %>% 
  group_by(cyl, gear) %>%
  do(data.frame(nrow=nrow(.)))

This is equivalent to using count():

library(dplyr, warn.conflicts = FALSE)
all.equal(mtcars %>% 
            group_by(cyl, gear) %>%
            do(data.frame(n=nrow(.))) %>% 
            ungroup(),
          count(mtcars, cyl, gear), check.attributes=FALSE)
#> [1] TRUE