GitHub - phillip1029/marketing-analytics-with-python: Marketing Analytics with Python

use VS Code extensions:
- Markdown All in One
- Markdown Footnotes
create a virtual environment venv
activate the environment venv and pip install -r requirements.txt
For the sample datasets, we use the dataset package ucimlrepo: pip install ucimlrepo
For data wrangler: use vs code extension 'data wrangler' by microsoft
format reference: https://jupyterbook.org/en/stable/content/components.html

Name		Name	Last commit message	Last commit date
Latest commit History 14 Commits
.github/workflows		.github/workflows
data		data
.gitignore		.gitignore
_config.yml		_config.yml
_toc.yml		_toc.yml
chapter_1.md		chapter_1.md
chapter_10.ipynb		chapter_10.ipynb
chapter_11.ipynb		chapter_11.ipynb
chapter_12.ipynb		chapter_12.ipynb
chapter_13.ipynb		chapter_13.ipynb
chapter_14.ipynb		chapter_14.ipynb
chapter_15.ipynb		chapter_15.ipynb
chapter_16.ipynb		chapter_16.ipynb
chapter_17.ipynb		chapter_17.ipynb
chapter_18.ipynb		chapter_18.ipynb
chapter_19.ipynb		chapter_19.ipynb
chapter_2.ipynb		chapter_2.ipynb
chapter_3.ipynb		chapter_3.ipynb
chapter_4.ipynb		chapter_4.ipynb
chapter_5.ipynb		chapter_5.ipynb
chapter_6.ipynb		chapter_6.ipynb
chapter_7.ipynb		chapter_7.ipynb
chapter_8.ipynb		chapter_8.ipynb
chapter_9.ipynb		chapter_9.ipynb
intro.md		intro.md
logo.png		logo.png
readme.md		readme.md
references.bib		references.bib
requirements.txt		requirements.txt
results\Chapter9_eda_report.html		results\Chapter9_eda_report.html

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