FROM DATA TO THESIS: Using Python for Non-Technical
Playground, Chapter 3: Data Manipulation and Cleaning with Pandas

How to use this project
1. Open this folder in VS Code (or your preferred Python editor/Jupyter environment).
2. Open exercises.py. It has four parts:
   A. Practise the chapter       the book's exercises, with blanks (______) to fill
   B. Go further                 new exercises beyond the book
   C. Check your understanding   short questions to answer in your own words
   D. Do it yourself             open tasks: no starter code and no answers
   Run in VS Code using Shift+Enter (Send selection/line to Python Interactive terminal) or run the file directly.
3. Check parts A to C in solutions.py, after you have tried each one yourself.
   Part D has no solutions: the tasks are open, as in your own thesis.

Files
- exercises.py        the four parts, with starter code for parts A and B
- solutions.py        solutions for parts A and B, model answers for part C
- students.csv        baseline cohort data (600 students, one row per student)
- semesters.csv       repeated semester measurements (2,326 rows)
- supervisors.csv     academic supervisors dataset (120 supervisors)
- questionnaire.csv   baseline 22 Likert survey items
- wellbeing_raw.xlsx  raw uncurated survey export

Please note: Elaf and her data are fictional. The data was generated by a
computer program to look realistic, and its patterns were built in by the
author. It describes no real people and is not evidence about real students;
do not cite or use it as research findings.

All four parts can also be done in your browser at:
https://polla-fattah.github.io/data2thesis_python/playground/chapter03.html
