R Programming Fundamentals

Using dplyr Methods to Create Data Summary Tables

We will utilize the dplyr verbs to create complex data summary tables. In order to do so, the following steps need to be executed:

1. Load the diamonds dataset using the following code:

data(diamonds) 

2. Group the data by cut, color, and clarity, and find the number of observations at each combination of the three variables, as follows:

diamonds %>% group_by(cut, color, clarity) %>% summarise(n())

3. Find the mean and median price of diamonds by using the dplyr functions group_by() and summarise() as follows:

diamonds %>% group_by(cut) %>% summarise(mean = mean(price), median = median(price))

4. We can also filter out data we're not interested in quickly using dplyr methods. Say we don't want ...