Exercise

Average rating per course

A great way to recommend courses is to recommend top-rated courses, as DataCamp students often like courses that are highly rated by their peers.

In this exercise, you'll complete a transformation function transform_avg_rating() that aggregates the rating data using the pandas DataFrame's .groupby() method. The goal is to get a DataFrame with two columns, a course id and its average rating:

course_id avg_rating
123 4.72
111 4.62
… …

In this exercise, you'll complete this transformation function, and apply it on raw rating data extracted via the helper function extract_rating_data() which extracts course ratings from the rating table.

Instructions

100 XP
  • Complete the transform_avg_rating() function by grouping by the course_id column, and taking the mean of the rating column.
  • Use extract_rating_data() to extract raw ratings data. It takes in as argument the database engine db_engines.
  • Use transform_avg_rating() on the raw rating data you've extracted.