Project 1 — Financial Data Analysis
Prerequisites: Python in Chapter 2, data in Chapter 3, market instruments in Chapter 10 and return measurement in Chapter 11. Starting with monthly simple returns, identify the data and units, compound wealth, align monthly RF, calculate volatility, Sharpe and drawdown, then interpret fixed-window tables and figures.
Two distinct data objects
The current reader Notebook uses a Seed101 constructed panel of 180 months, labelled January 2010 through December 2024, with columns NoDur, HiTec, Enrgy and RF. Industry codes are method-example labels here. There are no French market observations, and the fixed RF of 0.001 is not an observed cash rate.
The original historical report uses the French publication snapshot frozen on October 5, 2026. Its main 2010–2019 window contains 120 months, with three additional 60-month descriptive segments. The report’s wealth values, industry rankings, negative results and figures retain their historical identities. The constructed run neither reproduces nor verifies those market values. Exercises 2 and 5 ask you to read this historical report.
Current execution entry
Prepare an independent reader-package environment using the reader guide, then run from the package root:
.venv/bin/python run_notebook.py projects/project01/notebooks/project01_financial_data_analysis.ipynb
The runner prints the location of the fresh-kernel execution record; the Notebook separately prints a unique UUID directory for method outputs. New constructed CSVs and figures are written only under the package’s runs directory, preserving the original report, data and images. The French branch is skipped by default; no data are downloaded.
Read in this order
- Reader guide: inputs, actions, outputs, formulas, axes and the source material for all six exercises.
- Notebook language projection: the accepted I3 numerical cells, with revised explanatory Markdown only.
- Data dictionary and original data manifest: constructed-column contracts, historical snapshot hashes, portfolio formation dates and the periods supplying classification codes.
- Historical report, six exercises and complete solutions: report-reading questions use the original snapshot; constructed results do not replace their answers.
- Historical configuration and historical QA: fixed windows, annualization conventions and the scope of the original checks.
- Project entry: the complete English guide, dictionary, historical report and exercises.
Historical course-work route
The original command from the working course root is .venv/bin/python projects/project01/run_project01.py. It depends on manifest-bound French ZIP archives, extracted CSVs and processed CSVs; the original production tests are at tests/test_project01_analysis.py. These are historical reproduction locations, separate from the current offline Notebook entry. Consult the report and QA for the original output identities. This revision neither runs nor regenerates them.
G01 data rights, subject and use remain unresolved, and G05/A10-B is unauthorized. Technical acceptance of the A10-A.1 protocol supplies neither data permission nor execution authorization. The user-supplied-data contract describes future input requirements; it does not enable a market branch in this reader run.