Using the pipe %>%

The pipe %>% can be used to perform operations sequentially without having to define intermediate objects. After redefining murder to include rate and rank.

library(dplyr)
murders <- mutate(murders, rate =  total / population * 100000, rank = (-rate))

in the solution to the previous exercise we did the following:

# Created a table 
my_states <- filter(murders, region %in% c("Northeast", "West") & rate < 1)

# Used select to show only the state name, the murder rate and the rank
select(my_states, state, rate, rank)

The pipe %>% permits us to perform both operation sequentially and without having to define an intermediate variable my_states

For example we could have mutated and selected in the same line like this:

mutate(murders, rate =  total / population * 100000, rank = (-rate)) %>% 
    select(state, rate, rank)

Note that select no longer has a data frame as the first argument. The first argument is assumed to be the result of the operation conducted right before the %>%

This exercise is part of the course

Data Science R Basics

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Exercise instructions

Repeat the previous exercise, but now instead of creating a new object, show the result and only include the state, rate, and rank columns in that order.
Use a pipe %>% to do this in just one line.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Load library
library(dplyr)

## Define the rate column
murders <- mutate(murders, rate =  total / population * 100000, rank = rank(-rate))

# show the result and only include the state, rate, and rank columns, all in one line, in that order

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