This lesson introduced you to aggregates in R using dplyr. You learned:
- How to calculate summary statistics with
- How to perform aggregate statistics over individual rows with the same value or values using
Let’s examine some more data from ShoeFly.com. This time, in addition to the
orders data, we’ll be looking at data about user visits to the website, stored in the
page_visits data frame. Inspect the columns of the data frames using the rendered notebook.
Find the average
price of an order in the
orders data frame using
summarize() and the
mean() summary function. Save the resulting data frame to a variable named
average_price and view it.
Don’t forget to include
na.rm = TRUE as an argument in the call to
page_visits data frame, the column
utm_source contains information about how users got to ShoeFly’s homepage. For instance, if
group_by statement to calculate how many visits came from each of the different sources. Save your answer to the variable
click_source, and view it.
Our Marketing department thinks that the traffic to our site has been changing over the past few months. Use
group_by to calculate the number of visits to our site from each
utm_source for each
month. Save your answer to the variable
click_source_by_month, and view it.