Load the dplyr package and the murders dataset.

library(dplyr)
library(dslabs)
data(murders)

You can add columns using the dplyr function mutate. This function is aware of the column names and inside the function you can call them unquoted:

murders <- mutate(murders, population_in_millions = population / 10^5)

We can write population rather than murders$population. The function mutate knows we are grabbing columns from murders.

1. Use the function mutate to add a murders column named rate with the per 100,000 murder rate as in the example code above. Make sure you redefine murders as done in the example code above (murders <- [your code]) so we can keep using this variable.

2. If rank(x) gives you the ranks of x from lowest to highest, rank(-x) gives you the ranks from highest to lowest. Use the function mutate to add a column rank containing the rank, from highest to lowest murder rate. Make sure you redefine murders so we can keep using this variable.

3. With dplyr, we can use select to show only certain columns. For example, with this code we would only show the states and population sizes:

select(murders, state, population)

Use select to show the state names and abbreviations in murders. Do not redefine murders and store this result in state_abb.