In the first chapter on R (Chapter 2, Driving Visual Analysis with Automobile Data with R), we walked through an analysis project that examined automobile fuel economy data using the R statistical programming language. This dataset, available at http://www.fueleconomy.gov/feg/epadata/vehicles.csv.zip, contains fuel efficiency performance metrics over time for all makes and models of automobiles in the United States of America. This dataset also contains numerous other features and attributes of the automobile models other than fuel economy, providing an opportunity to summarize and group the data so that we can identify interesting trends and relationships.
Unlike the first chapter on R, we will perform the entire analysis using Python. However, we will ask the same questions and follow the same sequence of steps as before, again following the data science pipeline...
