Teaching materials for the Applied Data Analysis (ADA) workshop at DHOxSS 2019.
Authors/Convenors:
- Giovanni Colavizza (University of Amsterdam)
- Matteo Romanello (EPFL)
| Day.session | Topic | Materials |
|---|---|---|
| 1.1 | Introduction | slides |
| 1.2 | Data formats and input/output | slides + notebook |
| 2.1 | The Python data analysis stack, pt. I | slides + notebook |
| 2.2 | Tidy data pt.I-II | slides + notebook |
| 3.1 | Tidy data pt.III | slides + notebook |
| 3.2 | The Python data analysis stack, pt. II | notebook |
| 4.1 | Applied data analysis, pt. I: The basics | notebook |
| 4.2 | Applied data analysis, pt. II: Visualization | slides + notebook |
| 5.1 | Applied data analysis, pt. III: Modeling | notebook |
| 5.2 | Applied data analysis, pt. IV: Advanced application | notebook |
Inspiration for ADA was given by the following courses/teachers:
- Ryan Cordell's Humanities Data Analysis http://s17hda.ryancordell.org/schedule/
- Massimo Franceschet's Dear Data Science http://users.dimi.uniud.it/~massimo.franceschet/ds/syllabus/syllabus.html
- Bob West's Applied Data Analysis (ADA) https://dlab.epfl.ch/teaching/fall2018/cs401
- Garrett Grolemund and Hadley Wickham, R for data science, https://r4ds.had.co.nz/index.html
- Julia Silge and David Robinson, Text mining with R: A tidy approach, https://www.tidytextmining.com