Course Analytics - Wrangling FutureLearn Data With Python and R
Course Analytics - Wrangling FutureLearn Data With Python and R
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Course Analytics - Wrangling FutureLearn Data With Python and R

Last updated on 2016-04-30

About the Book

Writing your own reports and building your own dashboards from scratch takes time but this handy recipe book contains a handy selection of code fragments and functions for creating your own reports and interactive dashboards.

Using Jupyter notebooks and RStudio, this book shows you how to get started creating your own data analysis and reporting toolkit with just a few lines of code using Python or R.

The recipes include all you need to get started, even without programming experience. But if you do feel as if you need some programming practice first, why not sign up for the [Learn to Code for Data Analysis](https://www.futurelearn.com/courses/learn-to-code) FutureLearn course, which introduces you to the Python package and many of the Python programming techniques used in this book.

About the Author

Tony Hirst
Tony Hirst

Tony Hirst is a Senior Lecturer in Telematics (whatever that means?!) at The Open University, UK, and open data and technology blogger at [OUseful.info](http://ouseful.info).

Table of Contents

  •  
    • Introduction
  • Part 1 - Jupyter Notebook Recipes (Python / pandas)
    • FutureLearn Stats Recipes - Jupyter Notebooks
      • Initialisation
      • Loading the Data
      • Notable Dates and Steps
      • Simple Reporting
      • Enrolment Summaries
      • Adding in Some Step Intelligence
      • Step Intelligence - Activity Measures
      • Step Intelligence - Social Activity in More Detail
      • Reporting on Social Activity
      • Exploring Study Sessions and the Time Spent in a Study Session
      • Scheduling Support
      • Quiz Diagnostics
      • Summary

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