DPLYR

Now that we have started to tidy up our data we can see that we have a need to transform this data. We may wish to add additional variables. Perhaps we also wish to only look at data that meets a certain requirement. The dplyr package allows us to further work with our data.

dplyr Functionality

With dplyr we have five basic verbs that we will learn to work with:

filter()

select()

arrange()

mutate()

summarize()

We also will consider:

joins

group_by()

For the purposes of this example we will consider looking at the package nycflights13. This is a dataset that has all flights in and out of NYC in 2013. We also will be using the dyplr package from tidyverse:

library(dplyr)
library(nycflights13)

On Your Own: RStudio Practice

Before moving onto the next portion. Take some time to consider the nycflights13 data. You can explore it with the following call:

library(nycflights12)
flights

Once you have spent some time looking at the data, move onto the next lesson.