Data Manipulation in R: Piping Operator

The piping operator '%>%' makes working with the code very easy and intuitive.
When we write:

x %>% f(y)

it essentially means f(x,y)

R Code

#Method 1: Normal method
group_by(filter(hflights, !is.na(TailNum),UniqueCarrier)
 
#Method 2 : Using the piping operator
hflights %>%
        filter(!is.na(TailNum)) %>%
        group_by(UniqueCarrier)

Let's say we want to find out which airline by TailNum has the highest flights outs of Houston ?

Code

> b <- hflights %>%
       filter(!is.na(TailNum)) %>%
       group_by(TailNum) %>%
       summarise(n_flights = n()) %>%
       filter(n_flights == max(n_flights))
> b
Source: local data frame [1 x 2]
 
  TailNum n_flights
1  N14945       971