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.
Topics documented in the material
- Eurostat HICP
- INSEE Labour Force Survey
- Data cleaning
- Missing values
- Pandas
- Parquet
- Reproducible notebooks
Resources
TD01
Readings & practical resources
Notebooks
- TD01 — Price indices: notebookJupyter notebook · Open resource
Complete downloads
- Complete folder — supports, code, data and supporting checksZIP · Open resource
TD02
Readings & practical resources
Notebooks
- TD02 — Unemployment: notebookJupyter notebook · Open resource
Complete downloads
- Complete folder — supports, code, data and supporting checksZIP · Open resource
TD03
Readings & practical resources
Supplements & readings
- TD03 — Wage data: dictionaryPDF · Open resource
Notebooks
- TD03 — Wage data: notebookJupyter notebook · Open resource
Data
- TD03 — Wage data: CSVCSV · Open resource
Complete downloads
- Complete folder — supports, code, data and supporting checksZIP · Open resource
TD04
Readings & practical resources
Supplements & readings
- Additional course notesPDF · Open resource
Notebooks
- TD04 — Dataset merges: notebookJupyter notebook · Open resource
Complete downloads
- Complete folder — supports, code, data and supporting checksZIP · Open resource
TD05
Readings & practical resources
Notebooks
- TD05 — Income distributions: notebookJupyter notebook · Open resource
Data
- cm03-salaires.csvCSV · Open resource
Practical instructions
- Session instructions — HTMLInteractive HTML · Open resource
Complete downloads
- Complete folder — supports, code, data and supporting checksZIP · Open resource