Searching for a straightforward way to do Stata's bysort tasks in R

dat <- read.table(header = TRUE, 
           text = 
'category    var1 
a            1     
a            2    
a            3     
b            4     
b            6  
b            8   
b           10    
c           11     
c           14      
c           17')


(dat <- within(dat, {
  var6 <- ave(var1, category, FUN = function(x) c(NA, diff(x)))
  var5 <- c(NA, diff(var1))
  var4 <- ave(var1, category, FUN = length)
  var3 <- rev(!duplicated(rev(category))) * 1
  var2 <- (!duplicated(category)) * 1
}))

#    category var1 var2 var3 var4 var5 var6
# 1         a    1    1    0    3   NA   NA
# 2         a    2    0    0    3    1    1
# 3         a    3    0    1    3    1    1
# 4         b    4    1    0    4    1   NA
# 5         b    6    0    0    4    2    2
# 6         b    8    0    0    4    2    2
# 7         b   10    0    1    4    2    2
# 8         c   11    1    0    3    1   NA
# 9         c   14    0    0    3    3    3
# 10        c   17    0    1    3    3    3

An answer using dplyr

library(dplyr)
dat <- dat %>%
 group_by(category) %>%
 mutate(var2 = ifelse(row_number() == 1, 1, 0))%>%
 mutate(var3 = ifelse(row_number() == n(), 1, 0)) %>%
 mutate(var4 = n()) %>%
 mutate(var6 = lag(var1, 1)) %>%
 ungroup() %>%
 mutate(var5 = lag(var1, 1))