Exercises, notebooks, and data
Data Analysis with Python — L3
Five applied sessions on price indices, unemployment, data cleaning, dataset merges, and income distributions, with source data and reproducible Python notebooks.
- Institution
- CY Cergy Paris Université
- Role
- Tutorial
- Level
- Undergraduate (L3)
- Academic year
- 2026/2027
- Language
- French · French-language material
Topics documented in the material
- Eurostat HICP
- INSEE Labour Force Survey
- Data cleaning
- Missing values
- Pandas
- Parquet
- Reproducible notebooks
Resources
TD01
TD01 — Price indices: instructions
PDF · 2 pages · 98.48 kB
TD01 — Price indices: notebook
Jupyter notebook · 7.73 kB
Complete folder — supports, code, data and supporting checks
ZIP · 84.23 kB
TD02
TD02 — Unemployment: instructions
PDF · 1 pages · 57.36 kB
TD02 — Unemployment: notebook
Jupyter notebook · 9.04 kB
Complete folder — supports, code, data and supporting checks
ZIP · 54.32 kB
TD03
TD03 — Wage data: instructions
PDF · 1 pages · 48.20 kB
TD03 — Wage data: notebook
Jupyter notebook · 8.67 kB
TD03 — Wage data: CSV
CSV · 386.06 kB
TD03 — Wage data: dictionary
PDF · 4 pages · 95.60 kB
Complete folder — supports, code, data and supporting checks
ZIP · 250.15 kB
TD04
TD04 — Dataset merges: instructions
PDF · 51.54 kB
TD04 — Dataset merges: notebook
Jupyter notebook · 6.77 kB
TD04 — Presentation slides
PDF · 1.00 MB
Additional course notes
PDF · 47.95 kB
Complete folder — supports, code, data and supporting checks
ZIP · 970.42 kB
TD05
TD05 — Income distributions: notebook
Jupyter notebook · 6.70 kB
TD05 — Income distributions: instructions
PDF · 57.02 kB
Session instructions — HTML
Interactive HTML · 28.42 kB
Complete folder — supports, code, data and supporting checks
ZIP · 63.58 kB
TD01 · Presentation slides forthcoming
TD02 · Presentation slides forthcoming
TD03 · Presentation slides forthcoming
TD05 · Presentation slides forthcoming