FROM DATA TO THESIS: Using Python for Non-Technical
Playground, Chapter 17: Reproducible Research

How to use this project
1. Open this folder in VS Code, Cursor, Positron, or PyCharm.
2. Activate your virtual environment and install dependencies:
     pip install -r requirements.txt   (or install pandas, scipy, statsmodels, shiny, matplotlib, seaborn)
3. Open results.qmd and click Render (or run `quarto render results.qmd`). Then open exercises.txt
   and work through the Quarto and Shiny tasks.
4. Run the interactive dashboard:
     shiny run --reload app.py
5. exercises.py holds the Python exercises of the playground page, in four parts
   (practise, go further, check your understanding, do it yourself); run lines
   interactively. Answers are in solutions.py.
6. Finished versions of the Quarto and Shiny files are in the solutions folder,
   for after you have tried.

Files
- results.qmd          a results chapter: inline numbers, a table, a figure
- faculty-report.qmd   a one-page report with a faculty parameter
- app.py               the wellbeing dashboard (run with `shiny run app.py`)
- references.bib       references for results.qmd
- exercises.txt        the Quarto and Shiny tasks
- exercises.py         the Python exercises of the playground page
- solutions.py         answers to exercises.py
- solutions/           finished versions of the Quarto and Shiny files,
                       and programme-report.qmd for Exercise 8
- students.csv         one row per student in the wellbeing study (600 students)
- semesters.csv        one row per student per semester

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do not cite or use it as research findings.

Browser exercises for this chapter are at:
https://polla-fattah.github.io/data2thesis_python/playground/chapter17.html
