This article will guide you through quickly transforming millions of rows of trace data into a wide format time series table. If you are still wondering about it then this article is for you.
This article will guide you through quickly transforming millions of rows of trace data into a wide format time series table using the power of mighty Pandas.
For this demonstration, I’ll be using the OULAD dataset from Open University. The full dataset, as well as a lovely data description, is available at the link above. This is a dataset about student activity in a virtual learning environment in online classes. It spans 2 years and four cohorts for each of 7 modules.
I’ve written about this dataset before, as it’s one of my favorites. You can read about some of my previous work building predictive models using this data in my article, Predicting Student Outcomes by How They Interact With Their Learning Environment.
Today we will be exploring the student_vle.csv file in the zipped collection. This file contains trace data for student interactions with online activities accessible in the learning environment. Each row represents one activity that the student completed and includes the number of clicks they made in that activity.
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