- Created a new Python script for analyzing historical stock data.
- Implemented functions to test normality of price and return distributions.
- Included functionality to compute and visualize the efficient frontier for a portfolio of stocks.
- Added comments and documentation for clarity and future reference.
- Created a new Python script for portfolio analysis using historical stock data.
- Implemented functions for normality testing of prices and returns.
- Added histogram plots for prices and returns.
- Included logic for random portfolio allocation and efficient frontier calculation.
- Updated `pyproject.toml` to include `pandas-stubs` for type hinting support.
- Modified `uv.lock` to reflect the addition of `pandas-stubs` and its dependencies.
- Set execution_count to null for specific code cells in 2025_TP_1_M2_ISF.ipynb to reset execution state.
- Replace output display of DataFrames with print statements in 2025_TP_1_M2_ISF.ipynb for better visibility during execution.
- Clean up import statements in 2025_TP_2_M2_ISF.ipynb by adding noqa comments for better linting and readability.
- Created a Docker Compose file to set up a MySQL container named M2_SQL_COURSE with an empty password and a database named TP.
- Added a Makefile with a target to execute a SQL script (TP1.sql) inside the MySQL container and log the output.
- Implemented the TP1.sql script to create tables for Magasin and Localite, insert initial data, and perform several queries.
