Exercise: Exploring mtcars dataset with Tidyverse

The mtcars dataset is a built-in dataset in R. It comprises 11 features of 32 automobiles from the 1974 Motor Trend US magazine. We will use it for this data wrangling exercise.

First, let’s check what the data looks like and the class of this data. You may check more details about mtcars with the help function.

# Data exploration
View(mtcars)
class(mtcars)
?mtcars

Since it is a data frame with row names, we will turn the row names into a column called car, then convert the data frame to a tibble called mtcars_tb.

# Turn row name to column and convert to tibble
mtcars_tb <- rownames_to_column(mtcars, var = "car") %>% 
  as_tibble()

Exercise

Perform the following data wrangling steps. You may concatenate several steps with %>% pipe, or do each step one by one. Name the final variable as mtcars_final.

  1. One of the columns is am. It indicates transmission status, where 0 refers to automatic, and 1 refers to manual. Extract cars with manual transmission status.

  2. We are only interested in these five columns: car, mpg, cyl, wt, am. Select only these five columns for further analysis.

  3. Some column names are not intuitive. Rename the cyl to cyclinder, wt to weight, and am to transmission.

  4. We want to order our data. Arrange the data first by cyclinder in ascending order, and then by mpg in descending order.

Check your result: if you finish the data wrangling successfully, the mtcars_final should have 13 entries with 5 features. The first entry should be Toyota Corolla, and the last entry should be Maserati Bora.

Answer key