Get startedGet started for free

Challenges with missing values

You may have noticed that the pivoted DataFrames you have been working with often have missing data. This is to be expected since users rarely see all movies, and most movies are not seen by everyone, resulting in gaps in the user-rating matrix.

In this exercise, you will explore another subset of the user ratings table user_ratings_subset that has missing values and observe how different approaches in dealing with missing data may impact its usability.

This exercise is part of the course

Building Recommendation Engines in Python

View Course

Hands-on interactive exercise

Turn theory into action with one of our interactive exercises

Start Exercise