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CHANGELOG.md

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Commonly Highlighted Issues

1. .pycache and .virtual_documents/reports are not properly named or ignored in .gitignore.

The data folder is receiving unnecessary folders, such as the .ipynb_checkpoints folder.

  • URL: GitHub - .gitignore
  • Fix: A .gitignore template was used, and additional files were added based on the project requirements.

2. Code chunks in the README.md are presented as normal text, making them hard to distinguish from regular text. Additionally, the paragraphs are not well indented. The local run instructions are unclear — for example, the line "After activating the environment, you can run the analysis script or Jupyter notebook called bank_marketing_analysis.ipynb" is ambiguous.

  • URL: GitHub - README.md
  • Fix: Indentation and paragraphing were improved for better clarity.

3. Function documentation is insufficient. It lacks descriptions for the parameters being passed, and some scripts do not have a main() function.

  • URL: GitHub - Source Code
  • Fix: A main() function was added to all scripts, and the documentation for the models was updated to include parameter descriptions.

4. Reproducibility issue: I was unable to run the Docker container using the provided instructions (see error message below). A few minor fixes identified during the local run:

  1. The path to the environment creation file is incorrect.
  2. The conda env create and conda activate commands are written on the same line, which is confusing. I recommend separating them.
  3. Step 3, which refers to running the .ipynb file, is no longer applicable and should be removed.
  • Fix: The Docker Compose file was updated to address these issues. As previously mentioned a git ignore was created. And the environment was updated.

5. There is no mention of third-party software used in the analysis (e.g., Python, Pandas) in the report.

6. The report file bank_marketing_analysis.qmd contains hardcoded values (e.g., report numbers), which prevent the code from being reproducible if rerun. For example, the following screen captures show the Discussion sections with hardcoded results.

  • Fix: Refactoring of the code is currently in progress to make it more reproducible.

7. General

  • Fix:Tests: Are there automated tests or manual steps described so that the function of the software can be verified? Are they of sufficient quality to ensure software robsutness?

Tests were written : https://github.com/UBC-MDS/BankMarketingPreditions-/tree/main/test

Data : https://github.com/UBC-MDS/BankMarketingPreditions-/tree/main/data

Data was made accessible as part of the repository. Chat gpt was used to modify the markdown code.